## The Opportunity

A range of soil and water management practices has evolved over the past several decades to address low levels of soil organic matter, as well as nutrient depletion and moisture stress.²⁴⁵ Many are obvious and fundamental practices of agriculture: adding fertilizers, irrigating, and plowing crop residues and animal manure back into soils. The challenge is to come up with practical and economical solutions for many poor farmers who cannot afford fertilizers, lack access to large irrigation systems, have little access to mechanization, start with low crop yields, and must choose between competing demands for crop residues, such as animal feed or domestic fuel.

We start by exploring three techniques that have shown particular promise in dryland areas of Africa: some forms of agroforestry, rainwater harvesting, and fertilizer microdosing. We then summarize the debate around “conservation agriculture,” and some ideas for new or revised approaches based on that debate.

### Agroforestry

Agroforestry is any form of farming in which farmers deliberately integrate woody plants—trees and shrubs—with crops or livestock on the same tract of land. The term is broad and can refer to any form of agriculture that uses woody plants, including rubber, fruit production, and cocoa. Here we focus on the incorporation of trees into production systems for row crop agriculture.

A major success has occurred with the rejuvenation of agroforestry parklands in the Sahel. Since the mid-1980s, farmers have assisted in the regeneration of trees across more than 5 million ha, particularly in Niger but also in Burkina Faso, Mali, Senegal, and Ethiopia.²⁴⁶

Although farmers have used a variety of trees, the species *Faidherbia albida* highlights the potential to use trees to restore soil fertility.

Because it fixes nitrogen, its roots fertilize the surrounding soil, and because the tree's leaves drop during the growing season, they avoid shading out crops while also adding more nitrogen and mulch. A number of studies have shown an increase in yields in the areas around these trees. In the Kantché district of southern Niger, a region with high levels of on-farm tree densities, a 2012 study found that farmers had produced grain surpluses every year since 2007, even in the below-average rainfall year of 2011.²⁴⁷

In addition to the Sahel, farms in Kenya, Zambia, and Malawi have also adopted *Faidherbia*, and studies have shown yield gains there too. For example, in Zambia, trial sites under *Faidherbia albida* canopies yielded 88–190 percent more maize than sites outside of canopies (Figure 13-1).

Well-managed agroforestry systems can generate benefits in addition to enhanced crop yields.²⁴⁸ For example, depending on the species, trees might provide fruit, nuts, medicines, and fiber—all important for direct human use. Large branches can be cut to make poles for home construction or to sell in local markets for additional income. Branch trimmings can be used for firewood. For example, *Leucaena leucocephala* trees, which grow at a rate of 3–5 m/ year and supply wood at a rate of 20–60 m³/ha/ year, are efficient producers of firewood.²⁴⁹ Seed pods and leaves can serve as fodder or forage for livestock; *Leucaena* hedgerows provide 2–6 tons of high-protein forage per hectare per year.²⁵⁰ Leaves can be sold in markets; leaves of one mature baobab in Niger's Mirriah district vary in value from US$28–US$70, an amount sufficient to buy at least 70 kg of grain in the market.²⁵¹ Among other benefits, agroforestry systems help farmers in drylands build some economic resilience to drought and climate change. When the crops fail, the trees continue to produce.
<figure><img src="image_111.png" /><figcaption>Figure 13-1 | Maize yields are higher under *Faidherbia* trees in Zambia</figcaption></figure>

Note: Average maize grain yields from trial sites under and outside canopies of mature *Faidherbia albida* trees across regions in Zambia.

Source: Shitumbanuma (2012).

Rainwater Harvesting

Without attention to soil and water conservation, the loss of rainwater due to runoff from denuded fields can be significant. In Mali, for instance, 70-80 percent of rainwater falling early in the rainy season is lost to runoff, and rainfall runoff takes away about 40 percent of the nutrients applied to the soil through organic and mineral sources of fertilizer.²⁵² A variety of simple, low-cost water management practices can effectively capture and collect rainfall before it runs off farm fields.²⁵³ By slowing water runoff, such practices help farmers adjust to fluctuations in rainfall. These "rainwater harvesting" practices include:

- Planting pits ("zaï")

- Half-moon-shaped, raised earthen barriers ("demi-lunes")

- Lines of stone placed along contours ("bunds")

- Earthen barriers or trenches along contours ("ridge tillage")

Yield improvements from rainwater harvesting can vary from 500 to 1,000 kg/ha, depending on other factors such as soil fertility management.²⁵⁴ Farmers in Burkina Faso using rainwater harvesting techniques such as stone bunds and zaï to capture rainfall and reduce runoff have increased their yields from 400 kg to more than 900 kg/ha in some studies.²⁵⁵ And combining techniques on the same farm can increase yields more than one technique on its own (Figure 13-2).²⁵⁶

Multiple studies indicate that rainwater harvesting can help buffer farmers from the effects of erratic and reduced rainfall and increase crop yields.²⁵⁷ In Mali, for instance, the practice of ridge tillage reduces rainfall runoff and helps to capture scarce rainfall in a dry year. The practice has resulted in soil moisture increases of 17-39 percent. Ridge tillage allows earlier sowing and prolongs vegetative growth by as much as 20 days, thereby increasing millet yields by 40-50 percent. Ridge tillage also has resulted in an increase of 12-26 percent in soil carbon, and an increase of 30 percent in fertilizer-use efficiency.²⁵⁸
<figure><img src="image_112.png" /><figcaption>**Figure 13-2** | A combination of rainwater harvesting practices is more effective at increasing grain yields than one practice (Burkina Faso)</figcaption></figure>

Note: These two groups of villages are located on the northern central plateau of Burkina Faso.

Source: Sawadogo (2006).

## Fertilizer Microdosing

Microdosing fertilizer is a complementary practice that involves applying often just a capful of fertilizer directly to crop seeds or young shoots at planting time or when the rains fall.²⁵⁹ Microdosing enables expensive fertilizer to go as far as possible with the least amount of waste. Approximately 473,000 smallholder farmers in Mali, Burkina Faso, and Niger have used the technique and have experienced increases in sorghum and millet yields of 44–120 percent, along with increases in family incomes of 50–130 percent.²⁶⁰

Field results indicate that combining agroforestry, water harvesting, and microdosing has significant promise.²⁶¹ Agroforestry increases soil nitrogen, organic matter, and moisture. Water harvesting helps improve soil moisture and recharge groundwater. Fertilizer microdosing adds phosphorus and potassium where soils lack these elements. When conducted in tandem, agroforestry and water harvesting prepare the soil for the fertilizer, maximizing fertilizer-use efficiency.²⁶²

## Conservation Agriculture

Conservation agriculture is typically defined as farming that involves three basic practices:

- Minimizing soil disturbance by reducing the amount of tillage: seeds may be planted into small excavated basins rather than into tilled soil, or seeds are drilled into fields ("no-tillage" planting).

- Retaining vegetation on fields after harvest: farmers leave crop residues on the field (the dominant practice in developed countries), mulch from trees or other plants is applied, and/or a cover crop is maintained during the dry season or winter.

- Rotating different crops on the same land: rotation is used particularly to include more legumes and thereby to build soil nitrogen, to the benefit of all crops in the rotation.²⁶³
Together, the goal of these techniques is to reduce
soil erosion, increase soil organic matter and moisture content, add nitrogen, and help control pests.

In theory, these practices should be available even to farmers who cannot afford expensive agricultural inputs. Development projects in Africa have often pushed these conservation agriculture methods, and farmers practicing them with the aid of such projects have often increased their yields significantly and been able to make more efficient use of fertilizer and water.²⁶⁴ The International Fertilizer Development Center, a U.S.-based NGO, has been encouraging these kinds of efforts in conjunction with some increased use of conventional fertilizers, and has reported large yield increases by farmers participating in its projects.²⁶⁵ Of course, even without external encouragement, farmers in Africa have historically intercropped nitrogen-fixing beans and rotated in soil-enhancing crops.

Yet, despite the promise of conservation agriculture, adoption rates have been modest, and many farmers abandon efforts after development projects end. In Zambia, for instance, official government policy has strongly encouraged conservation agriculture since the 1980s.²⁶⁶ Yet FAO studies examining practices in 2008 of two key traits—minimum soil disturbance and planting basins—found not only extremely low adoption rates of 5 percent nationwide, but also that 95 percent of farmers nationwide who had previously used these practices had abandoned them.²⁶⁷

Although studies of participants in development projects have often found large yield gains from conservation agriculture,²⁶⁸ more recent studies have argued that this favorable literature “is subject to (i) data from experimental plots, (ii) small data sets from a non-representative group of farmers, or (iii) selection or other endogeneity problems.”²⁶⁹ In a study of conservation agriculture in practice in Zambia, FAO found no consistent yield gains from changed tillage or maintenance of residues with the exception of farms in the drier, eastern part of the country, where the practices probably helped to preserve soil moisture.²⁷⁰ This FAO study also found

that yield gains from virtually all practices evaluated were often wiped out by unexpected periods of drought. Other analyses of conservation agriculture also find a lack of yield gains when they analyze farms that are not part of experiments directed by researchers.²⁷¹

These experiences have led many researchers to challenge conservation agriculture, even scientists who specialize in nitrogen-fixing crops or soil carbon.²⁷² In doing so, they have highlighted many practical obstacles to adoption of conservation agriculture practices:

- **Labor.** Without mechanization and access to herbicides, large reductions in tillage require a great deal more work. Tillage has traditionally been the main way of dealing with weeds, and lack of tillage necessitates either more use of herbicides or laborious hand-weeding. Caring for trees offsite and then mulching them and adding them to soils is also time-consuming. In the absence of mechanization, smallholder farming already requires massive labor efforts, and farmers tend not to have the time or desire to add to these efforts.

- **Caloric needs and agronomic challenges with legumes.** Legumes such as beans provide protein and flavor to diets, but they produce fewer calories than maize, cassava, or yams per ha. Farmers who are already short on calories have less potential to add beans. In much of Africa, beans also face disease problems or various challenges with soil fertility.²⁷³

- **Competition for residues.** Crop residues are major sources of animal feed, and even farmers who do not have livestock often allow other farmers with livestock to graze their fields.²⁷⁴

- **Uncertain yield effects.** At a minimum, uncertain yield effects make investments of both funds and labor risky.
**Short-term decreases in yield.** Even if and when practices add organic matter to soils, the added carbon tends to absorb and immobilize nitrogen. Unless farmers have increased access to nitrogen fertilizer, soil carbon practices will often lower yields in the short term, and in fact, building soil carbon will require additional nitrogen.²⁷⁵

These challenges do not mean that adding soil carbon by retaining residues or reducing tillage through conservation agriculture practices could not have advantages. Rather, these challenges mean that effects are complex, and merely urging farmers to incorporate these practices into their existing farming systems will often be unsuccessful.

## New approaches?

The technical potential to restore soils is not at issue. For many years, researchers have developed promising strategies for revitalizing African soils that tend to work both in research plots and often for the duration of aid projects with participating farmers.²⁷⁶ For example, researchers explored “enhanced fallows,” which involve planting trees or shrubs on farm fields for two or more years, and then plowing the biomass into the soils.²⁷⁷ Related efforts plant trees along field borders or in small plots and bring the biomass generated to the crop field.²⁷⁸ Research studies have demonstrated potential for large yield gains from these kinds of efforts.²⁷⁹

The challenge is that these approaches tend to require more labor and costs for inputs, and the practice may involve at least a temporary loss of income. As a result, African farmers have not adopted soil conservation practices enough even to stabilize, let alone reverse, current levels of soil degradation. The lack of wide-scale adoption suggests the need for new approaches. We believe two strategies may hold promise.

One approach is to focus more on the changes in farm practices and agronomic factors that would make soil-building strategies more profitable and practicable. They include mechanization to reduce labor demands, development of quality fodder grasses that can grow well in land areas other than typical cropland, timely access to fertilizer, and reductions in the diseases that heavily affect bean production.²⁸⁰

A second approach involves working incrementally on a farm to restore one small piece of land at a time. Incremental restoration reduces labor requirements and takes less farmland out of production at any one time. By concentrating resources, including labor, nitrogen, and available carbon, the hope would be to restore a small area quickly to the point where it will generate large yield gains, thus providing economic return soon enough to justify farmer efforts. With enough yield gains and use of nitrogen-fixing crops, such areas could potentially enter a “virtuous cycle” whereby soil carbon continues to build over time.

Another possible option involves various ways of converting residues or household wastes into biochar, a residue of pyrolysis similar to charcoal. Although there continues to be scientific debate and uncertainty, biochar appears to provide at least a more stable form of concentrated carbon to soils that can also provide other agronomic benefits.²⁸¹ Those benefits appear to include, at least for some soils, enhanced nutrient effectiveness, probably through enhanced cation exchange. Many tropical soils are acidic, and biochar can also benefit yields by reducing that acidity. The key challenge is finding an economical and practical mechanism for increasing the production and use of biochar. Again, the incremental approach to farm fields might provide a viable approach.
## Recommended Strategies

Experiences in sub-Saharan Africa and elsewhere underscore the importance of several strategies for scaling-up improved soil and water management practices. Four strategies hold particular promise:

### Strengthen understanding

Evidence of which practices truly work for farmers and help to restore productivity is weak in much of Africa. Data about the costs and benefits are mostly lacking for both technical and social outcomes and obstacles. One way to improve understanding is for donor agencies to build this kind of technical and socioeconomic analysis into their project budgets for monitoring and evaluation. Agroforestry seems to have particular potential, but no good system exists for systematically evaluating where and why farmers find agroforestry successful. A promising start is that the World Agroforestry Center has built a website for agroforestry in Africa to organize information in a systematic way. Further progress will require expanded funding to support stronger evaluations of agroforestry projects and use of this website to organize that information systematically.

### Increase communication and outreach

Practical methods exist to spread knowledge of conservation management.

**Amplify the voice of champions.** Champions of improved soil and water management practices should be identified and their voices amplified. Champions can come from the public or private sectors. Some of the most effective champions are farmers who have already adopted these practices.

**Facilitate peer-to-peer learning.** Farmers can learn from other farmers working under similar agroecological conditions. Over the past two decades, farmer-to-farmer visits for knowledge sharing have become increasingly common.

**Use technology to directly communicate with farmers.** Mobile phones are becoming a widespread tool for information sharing. The Web Alliance for Re-greening in Africa²⁸² has developed a “Web of Voices” that links the use of mobile phones with radio stations and the internet. Likewise, radio stations can air programs in which experienced farmers share their knowledge. In southern Tunisia, for instance, a regional radio station had a special weekly program during which farmer innovators shared their experiences and answered questions.

<figure><img src="image_113.png" /></figure>
## Support institutional and policy reforms

Accelerating the spread of improved soil and water management practices requires enabling policies and legislation. Specific recommendations include the following:

**Reform outdated and counterproductive forestry legislation.** Despite repeated attempts to enact reforms, the forest codes in Senegal, Mali, Burkina Faso, and other countries still contain many provisions that allow forest service agents to impose fines or to otherwise discourage farmers from investing in protecting or regenerating trees in agroforestry systems. Reforming these laws is difficult when it involves changes to provisions related to the taxes, fines, and permitting requirements that some forest agents exploit to supplement their meager incomes. These forest codes are intended to conserve remaining areas of natural forests and woodlands but, because they lack specific provisions governing the management of multipurpose trees in farming systems, they are liable to have a perverse effect that contributes to reducing tree cover in agricultural landscapes.²⁸³

**Establish more secure land tenure and management rights over trees.** Smallholder farmers will only adopt these improved soil and water management practices when they feel they can reap the benefits of the improved practices. This means that land tenure and forestry legislation need to eliminate ambiguities and ensure that farmers have secure rights to their land and the resources flowing from that land. These resources should include trees on cropland that have been protected, regenerated, or planted by farmers. And farmers should be allowed to freely harvest and market the full suite of products from their farming systems, including wood and nontimber forest products from agroforestry systems.

**Strengthen local institutions to improve natural resource governance.** Experience underscores the critical importance of developing the capacity of local institutions—such as traditional or modern village development committees—to negotiate and locally enforce rules governing access to and use of natural resources, particularly the protection and management of on-farm trees and of natural vegetation. This requires locally enforceable rules to sanction illegal cutting of trees, limit damage caused by livestock to on-farm trees, and control bush fires.²⁸⁴

## Pursue new models for increasing soil carbon in depleted croplands

Aid agencies and governments need to pursue new approaches for rebuilding soils, and we suggest considering the two strategies we discuss above. One involves working on the impediments to soil conservation measures (such as bean diseases) and boosting production of high-quality forage grasses as a substitute for crop residues. The other involves projects that focus on incrementally restoring fertility to small portions of farms, perhaps as small as one-tenth of a hectare, through comprehensive programs that bring together all of the components needed. They would include financial assistance to allow farmers to forgo the food production involved and adequate fertilizers to feed the microorganisms necessary to turn plant carbon into stable soil carbon. One advantage of such an incremental approach is that it would allow programs to assist many farmers within the same budget.

For more detail about this menu item, see "Improving Land and Water Management," a working paper supporting this World Resources Report available at www.SustainableFoodFuture.org.
<figure><img src="image_114.png" /></figure>
MENU ITEM: PLANT
EXISTING CROPLAND
MORE FREQUENTLY

One way to produce more food on existing cropland is to plant
and harvest crops on that land more frequently. The ratio of
the quantity of crop harvests in a year—the harvested area—to
the quantity of arable land is known as the “cropping intensity.”
Globally, FAO estimates cropping intensity at only 0.82 because
much cropland is kept fallow. This chapter explores the practical
potential for increasing cropping intensity and finds limited
information.
## The Challenge

Two factors influence global cropping intensity in different directions. The first is the amount of fallow land—cropland that is not harvested in a given year. The identification of land as fallow implies that cropland is being rested, which results in a cropping intensity of less than one. The second factor is the number of crop harvests per year. In some warm climates with irrigation or sufficient rainfall throughout the year, farmers plant and harvest two cycles of crops—and in a few locations three—each year on the same tract of land. Multicropping creates a cropping intensity greater than one. In Bangladesh, for example, farmers on average achieve 1.56 crop harvests each year per hectare of cropland.²⁸⁵

The need to increase food production and avoid expansion of agricultural land means that it is generally desirable to increase cropping intensity. In principle, if land is cropped once per year or once every several years, cropping it twice per year will produce more food, save land, and reduce GHG emissions. There are, however, three significant challenges.

One challenge is economic. Using a simple global crop model, IIASA has estimated that the potential for increasing double-cropping—even on rainfed lands—is large and that half of all land suitable for growing cereals could technically support two crops per year.²⁸⁶ “Suitable land” counts both existing cropland and potential cropland, including forests. However, this estimate includes any land capable of producing any crop with up to 10 percent of global average yields. According to FAO global estimates, approximately half of all double-cropped land is irrigated, and farmers probably plant two crops a year on only 6 percent of rainfed area.²⁸⁷ Unless farmers are missing opportunities, the realistic economic prospects for expanding double-cropping on rainfed lands must therefore be far more limited than those projected by IIASA.

Second, the prospect of increasing double-cropping through irrigation is limited at best, and even present levels may not be sustainable. For example, cropping intensity across India is already at 140 percent, with Punjab ranking highest among Indian states at 190 percent.²⁸⁸ However, because much

of India is experiencing increasing water shortages and falling groundwater reserves,²⁸⁹ it is not clear whether existing levels of double-cropping can even be maintained.

Third, some efforts to reduce fallow lands would come with large costs in carbon and habitat values, particularly in areas that practice long-term shifting cultivation. Under shifting cultivation practices, land is allowed to regrow natural vegetation, typically trees, to rebuild soil fertility. Both the root growth and eventual clearing and often burning of the trees adds carbon and nutrients to the soil. In the forest part of the cycle, the trees can provide substantial carbon storage and habitat value, creating a landscape with higher values for both on average.

According to a recent estimate, areas of shifting cultivation, both cultivated and fallow, currently cover 280 Mha of land.²⁹⁰ This same study found that although fallow periods during shifting cultivation are declining, which reduces the share of land that is forested on average in the shifting agricultural landscape, shifting cultivation is persisting as a system. In these areas, a shift to permanent or more regular cultivation is not carbon-free or without loss of habitat.

## The Opportunity

Increases in cropping intensity from 85 to 89 percent, based on FAO estimates, are already factored into our baseline projections. According to GlobAgri-WRR, this increase would avoid roughly 70 Mha of land clearing. FAO projects that irrigated lands will provide roughly two-thirds of this cropping intensity gain, presumably from an increase in double-cropping.²⁹¹ These estimates are based on the judgments of regional experts, but there is no documentation to evaluate them further.

Recent FAO data appear to suggest a much more rapid increase in cropping intensity than is suggested by its 2050 projection, which we rely on for this report. The data suggest that between 2000 and 2011 alone, increases in cropping intensity provided the equivalent of 101 Mha of cropland farmed each year, and in that way avoided the conversion of 101 Mha of land from forest or other carbon-rich ecosystems.²⁹² On this basis, some researchers
record a rapid escalation in cropping intensity.²⁹³ Unfortunately, for reasons we discuss in Chapter 10 on the land-use challenge, data on cropland extent submitted to FAOSTAT can be highly unreliable, which means the changes in cropping intensity are also unreliable (Chapter 10).

An alternative way to increase cropping intensity involves leaving land fallow less often. Adjusting for areas that are double-cropped, about 350–400 Mha of cropland were not harvested in 2009 according to FAOSTAT data.²⁹⁴ (This amount roughly matches the 450 Mha estimate based on 2000 data from a paper by Siebert et al. [2010] that attempted to analyze cropping intensity globally.) Planting this land more frequently would appear to provide a good opportunity to increase production without increasing land area. However, there are several limitations:

- As discussed above, some fraction of this land probably represents land in shifting cultivation, in other words, land with long-term fallows. More frequent planting would entail substantial environmental costs.

- According to maps by Siebert et al. (2010), fallow lands are concentrated in dry areas where rainfall is probably not sufficient to plant crops every year.

- Some fallow lands should actually be considered “abandoned.” For example, U.S. cropland includes lands enrolled in the U.S. Conservation Reserve Program, and most of these lands have been planted with grasses or trees for more than five years.²⁹⁵ Cropland also appears to include large areas of abandoned agricultural land in the former Soviet Union.²⁹⁶ Unlike truly occasional fallow land, abandoned land reverts to forest or grassland (according to what the soils and climate can support), which sequesters abundant carbon and provides other ecosystem services. One study estimated carbon accumulating at a rate of 2.45 tons of carbon per hectare per year on abandoned land in Russia.²⁹⁷ Returning this land to productive use may be preferable to plowing up the world's remaining intact ecosystems, but it still comes at an environmental cost.

Notwithstanding the broad uncertainty and potential adverse effects of some increases in cropping intensity, there clearly are opportunities for progress. Brazil, for example, has seen an increase of roughly 9 Mha of maize planted as a second crop between 2001 and 2016.²⁹⁸ Brazil appears to have substantial potential for more double-cropping, although one study has estimated that climate change will greatly undermine that potential.²⁹⁹

Overall, the data limitations bar any confident assessment of the potential or likelihood of increased cropping intensity, or of the environmental implications of such an increase. Increases in double-cropping and reductions in short-term fallow land area probably provide an important mechanism for holding down agriculture-driven land-use change. In some long-term fallow regions, more intense cropping of regularly cropped land might allow long-term fallow areas to permanently regenerate to forests or grasslands. But where and how such intensification of cropping occurs will determine its economic, social, and environmental merits.

We assume that with great effort, cropping intensity might be increased by 5 percent more to 93 percent. This level of increase would reduce cropland demand by roughly 81 Mha and reduce annual emissions from land-use change by 646 Mt CO₂e, relative to baseline.

## Recommended Strategies

Analysis of the potential to reduce fallowing or increase double-cropping is so limited that making recommendations is difficult. Nonetheless, one obvious recommendation is for scientists and agronomists to conduct more detailed analysis of realistic, potential increases in cropping intensity. These studies should be detailed and spatially explicit, meaning that they should build in data reflecting small-scale differences in weather and soils by location. They should also account for limitations on irrigation water availability and build in at least some basic economic calculations. Only with this type of analysis can governments and researchers determine which improvements in infrastructure or crop varieties can contribute to making increased cropping intensity economically viable.
<figure><img src="image_115.png" /></figure>
CHAPTER 15

ADAPT TO
CLIMATE CHANGE

This course has focused on efforts to boost livestock and
crop yields on existing agricultural land, but such efforts will
not occur in a static world. Technology is changing but so is
the world's climate. In this chapter, we explore priorities for
agricultural adaptation to climate change. While priority actions
sometimes require targeted interventions, they often overlap
with and reinforce the need to implement other production-side
menu items presented in this report.
## The Challenge

Climate change and agriculture are a two-way street: “business as usual” growth in food production adversely affects the climate, but climate change itself poses challenges by adversely affecting food production. FAO’s projections of crop yield growth, which we incorporate into our 2050 baseline, make no attempt to account for climate change. Yet the world is on track for warming by 0.5–2 degrees Celsius (°C) or more by 2050 relative to preindustrial conditions and probably greater than 4°C by 2100.³⁰⁰ In 2007, the Intergovernmental Panel on Climate Change (IPCC) reported that

scientists projected, on balance, that climate change would lead to net global yield gains in 2050 due to beneficial conditions for cropping in the temperate zone.³⁰¹ But by 2014, new research had convinced the IPCC that, with a warming of 2°C above late-twentieth-century levels, average global crop yields are “more likely than not” to decline by at least 5 percent by 2050—with even steeper yield declines by 2100 (Figure 15-1).³⁰²

Overall, climate change will adversely affect yields in a few basic ways: through changes in temperature, changes in rainfall patterns, and sea level rise.

<figure><img src="image_116.png" /><figcaption>**Figure 15-1** | Negative impacts of climate change on crop yields are projected to become increasingly likely throughout this century</figcaption></figure>

*Note:* This figure includes projections for different emission scenarios, for tropical and temperate regions, and for adaptation and no-adaptation cases combined.

*Source:* Porter et al. (2014), Figure 7-5.
Temperature

Higher temperatures at critical times have direct effects on the growth of some crops. Most studies have focused on maize and wheat, yet tea and Arabica coffee are other clear examples.³⁰³ Much of researchers' increasing pessimism about climate effects on crops results from an increased understanding of the direct consequences of heat.³⁰⁴ For example, just a few days of exceptionally high temperatures at critical periods of growth, such as vulnerable reproductive stages, will reduce yields.³⁰⁵

Warmer temperatures are likely to change the distribution of pests and pathogens and either reduce or cause timing mismatches with pollinators³⁰⁶ in ways that reduce crop yields. Warmer winters reduce overwintering mortality of some insects and promote their early maturation.³⁰⁷ This results in earlier predation and an increase in the spread of plant pathogens by insect vectors.³⁰⁸

Higher temperatures dry out the atmosphere and soils due to evaporative loss, which, in turn, increases the rate at which plants transpire and therefore lose water.³⁰⁹ Although warmer temperatures will mean greater rainfall globally somewhere, these conditions will lead to greater water deprivation in other areas. Even in areas that do not dry out on average, this enhanced drying will increase the frequency of days when crops do not have optimal access to water.

Rainfall

In some regions, overall drier conditions will result in shorter growing seasons and increase the risk of large losses or absolute crop failures, although in some colder regions growing seasons will lengthen due to increased frost-free days.³¹⁰

More of the rainfall that occurs will take place in intense storms.³¹¹ Even in relatively “normal” rainfall years, the result will be more days with insufficient soil moisture levels and more problems related to floods and erosion.

Serious droughts and floods will also become more frequent, with the areas affected by drought disasters projected to grow from 15 percent to approximately 44 percent of the planet.³¹² Regions facing the greatest increases in instances of drought disaster include southern Africa, the United States, southern Europe, Brazil, and Southeast Asia. One study found that droughts caused annual average losses in global cereal production of 6.7 percent from 1964 to 1984. Losses rose to 13.7 percent between 1985 and 2007.³¹³ Regional models for sub-Saharan Africa indicate that maize yields could decrease by more than 50 percent in some areas by 2050 due to increased aridity.³¹⁴

Water stress on cropping, already significant in some areas, is likely to increase due to both growing water demand and climate change (see Figure 1-5).

<figure><img src="image_117.png" /></figure>
## Sea level rise

Sea level rise will result in saltwater inundation of agricultural land and saltwater intrusion into coastal aquifers that irrigate coastal crops. With a 1 meter (m) rise in sea levels, almost 11 percent of South Asia's agricultural land is projected to be vulnerable to flooding.³¹⁵

Climate change will also have some positive effects. First, even as some regions become drier, others will become wetter—which is generally beneficial for crop growth.³¹⁶ Second, higher temperatures in some colder, temperate areas will allow for longer growing seasons. Studies in northern China, for example, have projected significant benefits as warming temperatures enable two crops per year.³¹⁷ Third, higher atmospheric CO₂ concentrations stimulates plant growth by raising photosynthetic activity in many crops, increasing nitrogen use efficiency, and decreasing water use.³¹⁸ Expected benefits from these three effects largely explain why the IPCC as late as 2007 expected positive net effects on global crop yields in the relatively more moderate warming previously expected by 2050.

Over time, however, the weight of the evidence has shifted. Governments funded a series of outdoor experiments in which equipment sprayed out additional CO₂ to test how crops and other plants responded. Although the experiments confirmed much of what indoor trials had shown, researchers found roughly half of the expected yield gain in crops overall, in part because crops funneled a smaller than expected portion of their additional total growth into edible parts.³¹⁹ This lower expectation of the benefits of CO₂, combined with increas-

ing evidence of harsh effects of higher temperatures and more variable rainfall, shifted the overall estimate of yield impacts of climate change—even at moderate warming levels—to negative.

## The problem of uncertainty

Although the evidence is increasingly pessimistic, estimates of the scale of global impacts are highly uncertain and regional and local impacts are even harder to estimate. Uncertainty results from three core issues.

First, the degree of warming is uncertain because of gaps in our understanding of how the climate changes in response to concentrations of CO₂ that are higher than those prevailing over the past 100,000 years (although this uncertainty about warming has less effect on crop model projections than uncertainty about precipitation changes).

Second, the complexity of regional climate patterns generates great uncertainty in climate models, particularly those that attempt to estimate changes in precipitation as discussed below. Scientists try to overcome differences in model outputs by using suites of models; however, this approach mainly helps to better define the greatest areas of uncertainty and does not necessarily produce more accurate estimates. This uncertainty applies not merely to changes in average conditions but also to variability, which is important to crop responses.

Third, estimates of changes in crop yields due to a changing climate vary because crop models differ.

The high level of uncertainty in projections should actually be a cause for even more serious concern
because we have no assurance that the midrange projections are the most likely. Several studies project far more serious impacts. For example, a 2012 World Bank study estimated that by midcentury, global yields of wheat, maize, and soybeans could decline by 14–25 percent, 19–34 percent, and 15–30 percent, respectively, with a warming of 2.2°C to 3.2°C compared to preindustrial temperatures.³²⁰

The midrange IPCC projection of yield effects also relies primarily on crop models, whereas analysis using statistical models sometimes projects larger effects. Crop models attempt to simulate dynamic processes of crop growth and their response to variations in soil quality, radiation, rainfall, and temperature. Statistical models mostly relate crop yields to past trends in temperatures and rainfall. One statistical study in 2009 found dramatic effects on yields of maize, soybeans, and cotton in the United States for each cumulative total of 24 hours during the growing season that temperatures rose above 29°C. Using this relationship, the study indicated yield losses of 30–46 percent by 2100 under the most favorable (least warming) climate scenario and by 63–82 percent under the most rapidly warming scenario.³²¹ Another recent study projected that climate change could eliminate all trend line growth in overall agricultural productivity, or total factor productivity, by 2050.³²²

There is also growing evidence that crop yields have already declined because of climate change.³²³ In one analysis, statistical models linking crop yields to weather from 1980 to 2008 showed that declines and increases in soybean and rice yields balanced

out on a global scale, they also indicated that climate change depressed the growth in yields of maize by 3.8 percent and of wheat by 5.5 percent.³²⁴ In some countries, according to this analysis, estimated climate change effects were significant enough to freeze yields and thereby cancel out all benefits of improving technology.

Behind the global effects lie more serious regional food security concerns, because a substantial body of evidence indicates that the worst consequences of climate change are likely to be felt in sub-Saharan Africa and South Asia, the two most food-insecure regions of the world.³²⁵ Some crops such as cassava and peanuts might actually increase yields under climate change, although the effect would likely be highly variable across crop varieties and regions.³²⁶ However, cereal yields will most likely decline. One study using a crop model projects wheat declines in sub-Saharan Africa of 23–27 percent by 2050.³²⁷ Some important cash crops—such as coffee and cocoa—will no longer thrive in parts of their present growing areas.³²⁸ Efforts to move these crops to higher elevations will threaten forests in mountain areas, further contributing to GHG emissions.³²⁹

Shorter growing seasons may be even more of a problem in Africa. Growing seasons measure the periods when temperature and rainfall are adequate to produce crops, and Africa's short growing seasons are already a challenge for agriculture and food security. One study projects greater than 20 percent declines in the length of growing seasons in much of sub-Saharan Africa (Figure 15-2).³³⁰ Combining shorter growing seasons with increased variability in rainfall would make farming substantially riskier.
<figure><img src="image_118.png" /></figure>

Source: Verhage et al. (2018), using methods from Jones and Thornton (2015).

All of these changes combine to pose serious risks to food security, particularly by increasing the volatility of food supplies and prices.³³¹ Studies generally predict that climate change will lead to increased food prices by 2050, with estimated average price increases ranging from 3 percent to 84 percent—a wide range—relative to a world without climate change.³³² Nelson et al. (2009) estimated

that, due to climate-related price increases, the number of malnourished children under the age of five could increase by roughly 20 percent by 2050, relative to a world without climate change.³³³ Lloyd et al. (2011) estimated increases in moderate stunting of up to 29 percent and in severe stunting of 23 percent to 62 percent by midcentury relative to a world with a stable climate.³³⁴
## The Opportunity

The quantitative estimates of climate change impacts cited above generally assume no adaptation. What potential exists for adaptation and what can the world do now to take advantage of that potential? A number of researchers have used crop models to make quantitative estimates of adaptation potential (Box 15-1), primarily by modeling effects on yields if farmers changed crop varieties or were able to irrigate. These analyses suggest substantial potential to adapt, but the range of estimates remains large, and there are significant reasons to doubt the most comforting estimates. The major practical problem in formulating adaptation plans today is that regional climate models typically make widely varying predictions about changes in regional and local precipitation. For example, models disagree about whether West Africa will be wetter or drier,³³⁵ how rainfall will be distributed between the two monsoons in Sri Lanka,³³⁶ and how changes in climate oscillations such as El Niño will affect intraseasonal extreme rainfall in the contiguous United States.³³⁷ Even where models agree, there is uncertainty. For example, although most models predict that southern Africa will become drier, it actually appears now to be becoming wetter.³³⁸ In some locations, even if rainfall increases, the increased losses of water from soils and plants because of higher temperatures may make conditions for plants effectively drier.³³⁹ Because precipitation plays such a fundamental role in agriculture, these variations—with some exceptions—make it impossible to develop plans that are sufficiently reliable to guide changes in the types of crops farmers in the area should grow.

In part because of this constraint, the most important efforts needed are those improvements in farming that would be valuable regardless of climate impacts—what are known as “no regrets” strategies. For example, if farmers are better able

to manage the rainfall variability that exists today, they will be better able to handle the even greater variability that will exist tomorrow. If farmers have greater social security to deal with their risks today, they will be better able to deal with the increased variations in crop production likely to occur in the future.

In addition, in most cases, general improvements in farming will be more important than specific adaptation strategies for the simple reason that the former's scope of impact is potentially larger. For example, if farmers could raise yields by 50 percent using improved management to close a yield gap, an estimated 10 percentage point adverse effect of climate change would generally still leave a net gain of 40 percent in yield.

For these reasons, both researchers and policymakers have been struggling to separate actions that adapt to climate change from more general agricultural development strategies.³⁴⁰ Despite uncertainties, there are some clear, general patterns of climate change that greatly enhance the importance of resolving an existing agricultural challenge and that therefore merit special focus. Likewise, some climate-related physical changes in specific agricultural locations are sufficiently likely that major adaptation efforts can start—and in some cases have already started. We therefore focus on four adaptation measures that are specific applications of the menu items described in Chapters 12 and 13:

- Enable farmers to select alternative crop varieties

- Cope with rainfall variability

- Breed to overcome highly likely big climate challenges (e.g., extreme temperatures)

- Change land management practices to deal with predictable physical changes
## Improve incremental crop breeding and systems for farmers to select alternative crop varieties

One lesson from the adaptation analyses discussed in Box 15-1 is that, as the climate changes, farmers will often be able to lessen effects on yields by switching to alternative crop varieties that already exist somewhere in the world. But for many farmers, selecting new seed varieties is not as simple as picking a different seed each year from a catalog. Researchers are modeling seed traits that exist somewhere but that are not necessarily both adapted and available to each local condition. For farmers to be able to adapt, therefore, they need effective regional breeding systems to adapt varieties to the regions, and they also need to better marketing systems for acquiring seeds.

As Atlin et al. (2016) point out, “The best predictor of the climate in the very near future, (i.e. the next ten years) is the current climate . . . [so] farmers who are at least risk with respect to climate change are [therefore] those who use varieties bred very recently.” Therefore, as climate evolves over time, “the most important climate change adaptation tools for crop production are thus breeding and cultivar delivery systems that rapidly and continuously develop new varieties and replace old ones.” In general, these incremental breeding systems and seed distribution networks are weakest in sub-Saharan Africa, as discussed in Chapter 12. Climate change enhances the importance of improving them.

## Cope with rainfall variability through improved water management

Higher rainfall variability will be a nearly universal phenomenon of climate change. Farmers will face longer periods of droughts, more frequent torrential storms, and a general trend toward more concentrated delivery of regular rainfall.341 Farmers can adapt somewhat to this variability by shifting planting dates. Greater understanding of climate patterns and improved weather forecasting may help farmers plan their annual cropping decisions appropriately.

Many farmers would also benefit from enhanced irrigation. Unfortunately, for reasons discussed in “The Scope of the Challenge,” we do not believe that major new irrigation projects meet our sustainability criteria or will be economically or technically feasible in most locations because of the level of current water shortages and the high share of extractable water already used for irrigation. But small-scale irrigation efforts such as small storage basins,342 small reservoirs, and direct river and groundwater pumping in locations where abundant water still exists are more environmentally benign. Small farmers in sub-Saharan Africa have particularly undeveloped access to groundwater. One study estimated that small-scale irrigation could be economically expanded by roughly 100 Mha in the region, benefiting between 113 million and 369 million people.343 In addition, farmers can benefit from the rainwater harvesting techniques described in Chapter 13.
BOX 15-1 | Quantitative estimates of adaptation potential

To provide quantitative estimates of the effects of adaptation, researchers can use "process-based" crop models and estimate how crop yields would change not only under a different climate but if farmers adapted by using different crop varieties or irrigation. Process-based models simulate the different biological processes in plants and how they are influenced by factors such as rainfall, soils, and temperature; they therefore can estimate how plants with different growing seasons or other rainfall or temperature needs would respond. They differ from statistical models, which try to use direct evidence of how crop yields in the real world have varied with weather changes over time. Although different models generate varying results, the majority show a high potential for avoiding many of the worst impacts.

A comprehensive comparison of models has now calculated that adaptation could fully offset expected cereal declines of roughly 20 percent caused by temperature effects.ª On average, models also estimated that adaptation could offset half of declines due to changes in precipitation. These analyses on the whole suggest enormous potential for adaptation, mostly from the relatively modest effort of selecting alternative crop varieties or changing planting dates.

Looking at these process-based models in more detail, however, leads to more cautious conclusions:

* Even with adaptation, the average projection of these models indicates adverse effects on rainfed crops due to changes in average precipitation.

* Regional effects would still be severe for some crops after adaptation. For example, averaging multiple studies to estimate temperature effects still projects an almost 10 percent decline in maize yield in tropical climates in a world experiencing a 2°C increase over preindustrial average temperatures.ᵇ

* Just as the overall effects of climate change vary from model to model, so do the benefits of adaptation. Some studies still project adverse effects on global cereal yields of 30 to 40 percent with a temperature increase of 2-3°C.ª Because models make different predictions, it is natural to focus on some form of "average" results. But no statistical rule applies here to make the average more likely, and it is quite possible that some of the worse results will turn out to be more accurate.

Lobell (2014) summarizes several reasons to believe that these adaptation analyses are overly optimistic. Process-based models often leave out many of the features that climate change may adversely affect, such as temporary temperature extremes and variability in moisture conditions. Some adaptation studies analyze the benefits of adaptation measures without distinguishing whether they are effective in dealing with climate change or just in improving agriculture in general. A new crop variety or irrigation scheme may boost crop yields

regardless of climate change. Although implementing such improvements can be important, all measures to boost yields in effect help to compensate and therefore "adapt" in a broad sense to climate change. To analyze the effect of "adaptation" alone, we need to measure only the additional effect a measure would have as a result of a changing climate.

Perhaps most significantly, many studies using statistical models find significant adverse effects from climate change on current crop yields in the United States and Europe already. In these regions, farmers have a wide choice of seed selection, can regularly upgrade their seed varieties, and have detailed information about which varieties perform best in specific localities. If switching crop varieties were enough to offset adverse effects of climate change, these adverse effects should not be occurring.

Overall, the evidence from crop models does suggest significant capacity to adapt. But there is high uncertainty about the extent to which adaptation can offset the adverse effects of climate change, and it is doubtful that currently available forms of adaptation—although significant—can fully offset these adverse effects.

Sources:

a. Challinor et al. (2014).

b. Lobell (2014).
## Breed new traits to overcome large, highly likely climate challenges (e.g., extreme temperatures)

This recommendation concerns not simply improving the systems for incremental breeding but deliberately developing new traits. For example, despite many uncertainties, scientists have shown that maize and wheat are extremely sensitive to high temperatures, particularly during grain filling and silking—the reproductive stage during which grains are pollinated. Twenty thousand field trials in Africa have reported large maize yield losses for each 24 hours of temperature above 30°C, which typically occurs wherever average temperature during the growing season is 23°C or more.³⁴⁴ Rising temperatures are also likely to preclude Arabica coffee production in many midlevel mountain areas currently devoted to this crop.³⁴⁵ Breeding maize, wheat, and coffee to withstand higher temperatures is therefore urgently needed, but the task will not be easy because, at this time, all existing varieties of these crops exhibit temperature stresses.

Some crop breeding needs for adaptation fall into the category of fundamental crop research, which may have low odds for success but high potential for gains. For example, one study has projected that hotter, drier climates and increasing plant transpiration could lead to water shortages in the U.S. corn (maize) belt, where farmers use limited irrigation.³⁴⁶ Adaptation could include breeding for a variety of sophisticated changes in metabolic plant processes to reduce transpiration rates.

These kinds of adaptations require innovative genetic tools and breeding systems along with well-trained plant scientists. Breeders need to receive sufficient resources and concentrate efforts to breed greater resilience to the already identified and likely climate change effects. Encouragingly, there are already some modest efforts in this direction.³⁴⁷

## Change land management practices to deal with likely physical changes (e.g., sea level rise)

Rising sea levels are among the certain impacts of climate change. In recent years, rapid ice melt in Antarctica has surpassed expectations, leading to augmented projections that, if emissions remain high, sea levels would most likely rise 1.5 m and possibly more by 2100.³⁴⁸ In addition to much larger areas that become vulnerable to occasional flooding, one study indicates that sea level rise of 1 m would inundate roughly 0.4 percent of agricultural land in developing countries (roughly 6 Mha), and a rise of 2 m would inundate about 0.7 percent (roughly 12 Mha).³⁴⁹ While these global percentages are low, effects would be harsh for farmers and economies at the local level. In Bangladesh, agriculture has already experienced adverse impacts due to saltwater inundation and salinity intrusion, resulting in a conversion of 500 ha of agricultural land per year (in the study area) to saline land and a decline in rice production.³⁵⁰ The coastal areas of the Mekong Delta in Vietnam are similarly experiencing saltwater intrusion.³⁵¹
In these areas, work to build resilience has already started. In Bangladesh, efforts include coastal afforestation, cultivation of saline-tolerant crops, homestead and floating gardens, embankment cropping, and shifts in livelihoods, including to shrimp farming.352 In Vietnam, agricultural changes have been mainly driven by national-level policies. Physical infrastructure projects appear to be the favored approach to minimizing the effects of sea level rise, but there has been a combination of adaptation activities, including upstream flow control, agronomic measures, and regeneration of coastal ecosystems.353 In both Bangladesh and Vietnam, fully inundated areas may require transitions to aquaculture, and the extent of inundation will determine the types of aquaculture that are feasible.

Although not certain, there is also a high risk that some of the drier arable lands in Africa will cross thresholds and become unsuitable for crop production due to decreased rainfall and/or greater rainfall variability. Africa already has highly variable rainfall seasons that result in short crop-growing seasons in many areas. Delays in rainfall, or periods of little or no rainfall during the wet season, can lead to high rates of crop failure. The aggregation of climate change impacts may lead to circumstances in which parts of Africa must abandon crop agriculture and transition to agropastoralism or pastoralism, which is capable of handling both drier and more variable rainfall conditions.354

## Recommended Strategies

Most needs for adaptation overlap with the menu items we discuss in this report and involve fine-tuning menu item strategies. For example, increasing food production in Africa requires improvements to incremental breeding and seed distribution systems, which would also help crops to evolve with changing climates. Building social welfare systems would allow small farmers to withstand periods of hardship without selling their assets, and the need for resilience will increase with climate change. Many systems that are important today, such as small-scale water-supply systems in Africa and institutional capacity to respond to plant diseases, will only become more important in the future.

In some contexts, information about the future climate is sufficiently clear or local to call for specific new efforts that would otherwise not be justified. Examples include breeding new traits for many crops that enable them to handle high temperatures, and adjusting agricultural production in coastal areas affected by rising sea levels. Over time, as evolving weather patterns become clearer, more of these examples will emerge.

Overall, we believe countries and global organizations should view the need for adaptation as adding urgency to the broader menu for a sustainable food future.
<figure><img src="image_119.png" /></figure>
HOW MUCH COULD
BOOSTING CROP AND
LIVESTOCK PRODUCTIVITY
CONTRIBUTE TO CLOSING
THE LAND AND GREENHOUSE
GAS MITIGATION GAPS?

This chapter uses the GlobAgri-WRR model to explore the combined potential of the measures described so far in this course to limit agricultural land expansion and reduce agricultural GHG emissions, even as the world feeds a growing population.
The menu items in Chapters 12–14 (improve crop breeding, improve soil and water management, and plant existing cropland more frequently) all increase crop production per hectare to meet growing food demand while avoiding further land clearing and associated GHG emissions. What is the combined potential of these menu items? And to what extent might climate change hinder progress if the adaptation measures discussed in Chapter 15 are not pursued? Table 16-1 summarizes the effects of several crop yield change scenarios, based on the GlobAgri-WRR model. All scenarios but the final one in Table 16-1 hold cropping intensity constant from the 2050 baseline level. The final scenario uses the yield growth in our baseline but increases cropping intensity.³⁵⁵

Our analysis first shows that differing conceptions of an appropriate “2050 baseline” lead to vastly different amounts of future cropland expansion. A purely theoretical scenario that holds crop yields constant from their 2010 levels, and assumes no change in projected demand, would require cropland expansion of more than 950 Mha between 2010 and 2050 to meet projected food demand and accompanying high land-use-change emissions (more than 12 Gt CO₂e per year during that period). Using FAO’s projected growth in yields and cropping intensity (which follows historical trends from 1962 to 2006), as we do in GlobAgri-WRR, expansion is limited to 171 Mha and land-use-change emissions to 6 Gt per year. Using more recent and slower estimates of yield growth from 1989 to 2008 from Ray et al. (2013), cropland area would expand 301 Mha by 2050 relative to 2010, with annual land-use-change emissions of 6.9 Gt.

As discussed in Chapter 15, a changing climate has the potential to depress crop yields, especially in the tropics. We therefore explore a scenario with a 15 percent decline in crop yields across the board relative to our 2050 baseline projection.³⁵⁶ This scenario in effect would lower average global crop yield growth between 2010 and 2050 from 48 percent to only 28 percent.³⁵⁷ Thus, a “mere” 15 percent decline in yield would increase the necessary expansion in cropland during this period to 437 Mha, nearly tripling the cropland expansion relative to our 2050 baseline scenario. This large additional expansion would increase the land gap by 45 percent and the GHG mitigation gap by 23 percent, relative to the 2050 baseline.

On a more positive note, we model scenarios of additional increases in crop yields between 2010 and 2050

to simulate large-scale implementation of the crop breeding and soil and water management menu items discussed in Chapters 12 and 13. We model additional increases in crop yields that are 20 percent and 50 percent larger than those in our baseline, which would push global yield increases between 2010 and 2050 from 48 percent under our baseline projection to 56 percent and 69 percent, respectively. Such scenarios would represent enormous agricultural progress, as both would require more substantial yield increases than the historical period 1962 to 2006, which encompassed the Green Revolution, and would be achieved in a period of greater resource scarcity and under a changing climate.

The scenario that increases yields by 56 percent compared to 2010 would bring the amount of necessary cropland expansion between 2010 and 2050 down to 80 Mha. The scenario that increases yields by 69 percent would actually achieve a net reduction in cropland area of 39 Mha. Even this highest yield scenario, however, would only cut the land gap by 35 percent because it would not affect pasture.

Because sub-Saharan Africa is such an important “hotspot” for achieving a sustainable food future, as described in Box 2-4, we also examined scenarios of different levels of yield growth just for that region. Under our baseline scenario, cropland would expand by 102 Mha in sub-Saharan Africa, by far the most of any region.³⁵⁸ A scenario with 20 percent slower yield growth (relative to baseline) would increase the additional cropland demand in the region to 138 Mha. Going the other direction, 20 percent faster crop yield growth would lower the additional cropland demand in sub-Saharan Africa to 73 Mha.

Finally, although our 2050 baseline raises global cropping intensity from 85 percent in 2010 to 89 percent in 2050, we explore a scenario that increases cropping intensity to 94 percent. That additional increase would reduce cropland expansion from 171 Mha (under our baseline) to only 90 Mha, closing the land gap by 14 percent and the GHG mitigation gap by 6 percent.

At some level, the implications of these different scenarios are all the same: boosting yield growth and cropping intensity (at least for lands that are already regularly cropped) is critical to achieving a sustainable food future.
<table><caption>**Table 16-1** | Global effects of 2050 crop productivity change scenarios on agricultural land use and greenhouse gas emissions</caption><thead><tr><th rowspan="2">SCENARIO</th><th rowspan="2">CHANGE IN<br>CROPLAND AREA,<br>2010-50 (MHA)</th><th colspan="3">ANNUAL GHG EMISSIONS, 2050<br>(GT CO<sub>2</sub>E)</th><th rowspan="2">GHG<br>MITIGATION<br>GAP (GT CO<sub>2</sub>E)</th></tr><tr><th>Agricultural<br>production</th><th>Land-use<br>change</th><th>Total</th></tr></thead><tbody><tr><td>No change in crop yields from 2010</td><td>952<br>(+781)</td><td>9.6</td><td>12.2</td><td>21.8</td><td>17.8<br>(+6.8)</td></tr><tr><td><strong>2050 BASELINE (crop yields grow 48%<br>between 2010-50)</strong></td><td><strong>171</strong></td><td><strong>9.0</strong></td><td><strong>6.0</strong></td><td><strong>15.1</strong></td><td><strong>11.1</strong></td></tr><tr><td>Crop yields grow at 1989-2008 rates using<br>Ray et al. (2013)</td><td>301<br>(+130)</td><td>9.0</td><td>6.9</td><td>15.9</td><td>11.9<br>(+0.8)</td></tr><tr><td>15% global decrease in crop yields due to<br>climate change with no adaptation</td><td>437<br>(+265)</td><td>9.3</td><td>8.2</td><td>17.6</td><td>13.6<br>(+2.5)</td></tr><tr><td>20% additional global increase in crop<br>yields</td><td>80<br>(-92)</td><td>8.9</td><td>5.3</td><td>14.3</td><td>10.3<br>(-0.8)</td></tr><tr><td>50% additional global increase in crop<br>yields</td><td>-39<br>(-210)</td><td>8.8</td><td>4.4</td><td>13.2</td><td>9.2<br>(-1.8)</td></tr><tr><td>20% decrease in crop yields in sub-<br>Saharan Africa</td><td>207<br>(+35)</td><td>9.0</td><td>6.3</td><td>15.3</td><td>11.3<br>(+0.3)</td></tr><tr><td>20% additional increase in crop yields in<br>sub-Saharan Africa</td><td>142<br>(-29)</td><td>9.0</td><td>5.8</td><td>14.8</td><td>10.8<br>(-0.2)</td></tr><tr><td>5% additional increase in global cropping<br>intensity</td><td>90<br>(-81)</td><td>9.0</td><td>5.4</td><td>14.4</td><td>10.4<br>(-0.6)</td></tr></tbody></table>

Notes: Numbers not summed correctly are due to rounding. Numbers shown in parentheses are changes relative to 2050 baseline.

Source: GlobAgri-WRR model.
1. Mueller et al. (2012).

2. Alexandratos and Bruinsma (2012).

3. Alexandratos and Bruinsma (2012).

4. Evenson and Gollin (2003a).

5. For papers exploring the significance of this shift from draught animals in Austria, see Gingrich et al. (2007); and Gingrich and Kraussmann (2018).

6. According to FAOSTAT, East African maize yields were 1.79 t/ha/yr in 2010 and U.S. maize yields were 9.58 t/ha/yr.

7. Burney et al. (2009); Foresight (2011a).

8. Our calculations based on projections from GlobAgri-WRR and using FAOSTAT for historical growth.

9. The summary here is from Schmitz et al. (2014), Figure 1, scenario S1, which is defined as "no climate change and a medium pathway of economic growth and population development."

10. Schmitz et al. (2014), Figure 2.

11. To obtain a slight decrease in cropland area, Bajzelj et al. (2014) estimate a need both for closing most yield gaps and a 50 percent reduction in food loss and waste.

12. Tilman et al. (2011) do not split the agricultural land expansion between cropland and pastures.

13. Schmitz et al. (2014). The summary here is from the Figure 1, scenario S1, which is defined as "no climate change and a medium pathway of economic growth and population development."

14. OECD (2011).

15. Alexandratos and Bruinsma (2012); UNDESA (2017).

16. FAO yield growth rates are somewhat lower than historic global rates of yield growth but somewhat higher on average than regional rates of yield growth. Because it is not clear which rate of yield growth makes more sense to compare with history, we use the phrase "comparable to historical yield growth" as, in effect, an average of the two trend lines.

17. Ausubel et al. (2012).

18. See summary in Grassini et al. (2013).

19. Grassini et al. (2013).

20. Ray et al. (2013).

21. Ray et al. (2012).

22. Sands et al. (2014).

23. The GLOBIOM model runs we cite in this report assume an independent growth rate of crop yields, as well as an "endogenous" growth rate on top of that exogenous growth rate based on demand and price. For a discussion of the GTAP and MIRAGE models, see the supporting information in Searchinger, Edwards, Mulligan, et al. (2015).

24. GlobAgri-WRR model.

25. The basis for this analysis is set forth in Bodirsky et al. (2015).

26. Authors' calculations from FAO (2019a).

27. Lobell et al. (2009); van Ittersum et al. (2013).

28. Lobell et al. (2009).

29. Licker et al. (2010).

30. Lobell et al. (2009).

31. For example, if the top 10 percent of farms define the yield potential, then data errors that exaggerate that potential top 10 percent will result in larger gaps with other performers.

32. See Estes et al. (2013) for a comparison of different categories of crop models.

33. Foley et al. (2011).

34. Fischer et al. (2014).

35. For example, Fritz et al. (2010) shows large discrepancies in cropland maps in Africa from different satellite mapping products. For a discussion of the challenges and inconsistencies between satellite maps and more detailed methods, see Estes, McRitchie, Choi, et al. (2016). See also Li et al. (2010).

36. Hansen et al. (2013).

37. The computer-interpreted analyses from satellite photographs like Landsat at this time are less accurate than human interpretation of closer, aerial photographs. One mechanism for determining the accuracy of satellite interpretation is therefore to verify its projections in a particular location with those derivable from Google Earth photographs using the human eye. In Zeng, Estes, et al. (2018) the authors compared UMD-based projections with thousands of Google Earth photographs in Southeast Asia and found an accuracy of more than 90% for claims of forest-cover loss, and more than 80 percent for claims of nonforest-cover loss, which was much higher than analyses of a range of other land-cover products.

38. In Tyukavina et al. (2018), for example, the authors estimated a loss of 16.6 Mha between 2000 and 2014 in the Congo basin, of which 84 percent was attributed to agriculture, more than 90% of which was "rotational agriculture." In that paper, the authors made clear that while they believed the agriculture would be "rotational," it involved new agricultural expansion that would also be rotational so did involve net forest loss.
39. In Celine et al. (2013), the authors found gross deforestation in the Congo basin of 480,000 ha/yr from 2000 to 2005—twice the rate of the previous decade—and net deforestation of 317,000 ha/yr. The authors attributed some of the additional net deforestation to the reduced length of fallow in rotational agriculture.

40. Zeng, Estes, et al. (2018) shows regional patterns including northern Thailand. Zeng, Gower, et al. (2018) found large-scale deforestation in the Nan province of northern Thailand, 92 percent of which was crop fields.

41. Zeng, Gower, et al. (2016).

42. McNicol et al. (2018) found five times higher rates of deforestation for 2005–10 in the woodlands of southern Africa than in the Hansen data set, which we believe is based on a much lower canopy-cover threshold used to estimate forest in McNicol et al. (2018).

43. Searchinger, Estes, Thornton, et al. (2015) discuss agricultural expansion pressures in the savannas of sub-Saharan Africa; Lambin et al. (2013) discuss other savanna hotspots of conversion that include savannas, such as the Chaco dry forest.

44. The analysis employed by GFW did not distinguish what land that reforested had previously been, but two indicators explain why the substantial majority was likely reforesting from forestry or fire. One is that, unlike agricultural land, clear-cut or burned forest land is not maintained for some other use, and so is likely to reforest. Two, the analysis found that the leading areas with reforestation were Russia, the United States, and Canada, in all of which forest-cover loss is primarily due to forestry and fire.

45. The most important restriction was to count forest gains only when forests achieved 60 percent canopy cover. By contrast, forests are counted as lost if they had 30 percent canopy cover. The 60 percent canopy cover restricts the types of forests that could be counted, but it may also count increasing thickening of forests that already existed but not at 60 percent cover.

46. For example, maps produced by the European Space Agency Climate Change Initiative estimate a gross loss in forest area of only 4.5 Mha per year from 1992 to 2015, with even slower rates after 2000 (Li et al. 2017). Song et al. estimate net gains in forest in this period.

47. The images used in Li et al. (2017) are based on maps that are 9 ha in size, in contrast to the roughly one-tenth of a hectare Landsat maps used by Global Forest Watch. The maps generated by Song et al. (2018) have a pixel size of 2,500 ha and are based on multiple satellite image products, the primary one with pixels representing 121 ha. Many other analyses use Moderate Resolution Imaging Spectro-radiometer (MODIS) satellite images, which have a pixel size of 6 ha.

48. Estes et al. (2018) contains a thorough discussion of the challenges in using satellite images with pixels of different sizes and, by comparing them with a high-quality, local spatial data set, finds higher inaccuracies and systematic biases in mapping products based on these images with larger pixel sizes.

49. Estes et al. (2018).

50. FAO (2019a). These data are based on FAO-reported harvested areas for 159 crops, which are all the FAO-reported crop harvested areas except two small-area crops that had no reported data from early years.

51. To avoid bias with any one year, each year reported is actually an average of harvested area that year and in the one preceding and one subsequent year.

52. FAO (2019a). These are data for 2002 through 2016.

53. Foley et al. (2011); Babcock and Iqbal (2014).

54. This calculation is based on background data provided by the authors of Zalles et al. (2019) for Figure S9 of that paper, which is based on Brazilian government reported data on double-cropping.

55. According to FAO (2019a), China reported an increase in harvested area by more than 8.7 Mha between 2001 and 2013, and a decline in "arable" and "permanent" cropland by 4 million ha, for a net gain of nearly 13 Mha, roughly a 10 percent gain in cropping intensity.

56. Qiu et al. (2017).

57. Borchers et al. (2014). United States Department of Agriculture statistics. See Summary Table 3, https://www.ers.usda.gov/data-products/major-land-uses/major-land-uses/#Summary tables.

58. United States Department of Agriculture statistics. See Summary Table 3, https://www.ers.usda.gov/data-products/major-land-uses/major-land-uses/#Summary tables. The difference probably has much to do with a recategorization of land in a category called "cropland pasture."

59. This figure is the decline in land in the Conservation Reserve Program. U.S. Department of Agriculture, Farm Services Agency, "CRP Ending Enrollment by Fiscal Year, 1986-2018," https://www.fsa.usda.gov/programs-and-services/conservation-programs/reports-and-statistics/conservation-reserve-program-statistics/index (last accessed April 2019). Because this land would have been out of production for at least five years, it would not have been considered cropland according to the FAO definition and would therefore qualify as an increase in cropland when cropped.

60. The paper, Zalles et al. (2019), compared its analysis not with FAOSTAT but with cropping data reported by the Brazilian Institute of Geography and Statistics (IBGE) and found that, when deducting double-cropped areas, the discrepancy in cropland reduced to around 10 Mha in 2002 and 5 Mha in 2014. However, IBGE data on cropping are still nearly 20 Mha less than FAOSTAT in 2014, and only 7 Mha of that discrepancy might be explained by its not counting permanent crops, which FAOSTAT does count. That still leaves a 13 Mha gap.

61. Hua et al. (2016); Ahrends et al. (2017).
62. Fetzel et al. (2017).

63. This was the area in effect back-calculated from feed consumption and other sources of animal distribution by the authors of Herrero et al. (2013).

64. Ramankutty et al. (2008).

65. Erb et al. (2007).

66. Stadler et al. (2018).

67. FAO (2019a).

68. A recent summary for all of Latin America is Graesser et al. (2015). Local studies include Barona et al. (2010); Barreto and Silva (2010); Gasparri and Grau (2009); Killeen et al. (2008); and Redo and Mil- lington (2011). Although most studies find that expansion of pasture is the primary driver of forest loss in Latin America, Pendrill and Pers- son (2017) found conversion to pasture responsible for one-third of forest loss in Latin America from 2000 to 2011.

69. Graesser et al. (2015).

70. The increase in economic output is measured in dollars. As a result, increases in yields and total production of high-value agricultural products, such as milk, meat, fruits, and vegetables, count more in economic terms than increases in yields of cereals and other lower-value products, but this assumes constant prices for the different outputs. In theory, because the relative prices of different agricultural outputs vary, the specific time used to fix those prices could influ- ence these calculations. In reality, the growth of economic output does not vary much by this time frame.

71. Fuglie and Nin-Pratt (2012).

72. Fuglie and Nin-Pratt (2012).

73. FAO (2015b), 30.

74. GlobAgri-WRR model.

75. GlobAgri-WRR model.

76. GlobAgri-WRR model.

77. A major focus of the GlobAgri-WRR analysis was to project a baseline for ruminant livestock efficiency gains. Efficiency gains come in two forms. One is a reduction in the feed (in the form of dry matter) per kilogram of beef or milk. These gains can occur either because of improved animal management or breeds or improvements in feed quality, including more nutritious grasses and some switch to crop-based feeds. The other efficiency gain is in the quantity of feed consumed by animals per hectare. Neither of these figures is directly known historically. FAO estimates quantities of crop-based animal feeds back to 1961, but not grasses and other forages, nor does FAO estimate how much crop-based feeds were eaten by ruminants ver- sus other livestock. We therefore developed a statistical relationship for modern livestock systems between output of milk or meat per animal and output per unit of feed separately using data that went into both Wirsenius et al. (2010) and Herrero et al. (2013). Although these papers had different estimates, the relationship they estimated between efficiency per animal and efficiency per unit of feed was similar. From this relationship, we could estimate a rate of gain in output per unit of feed by 2050 of 20% for beef and 16% for dairy. This rate was global. We also did not believe that historical rates of improvement by region are relevant to future predictions because re- gions with the highest previous gains now face biological barriers to their rates of improvement. We programmed GlobAgri-WRR to find a resolution that achieves this level of feed efficiency gain within each region by switching livestock production systems to proportionately close gaps between their existing efficiency and the highest global efficiencies. We also assumed a level of yield gap growth in the highest systems of 3%. We also estimated the growth in output of grass per hectare of grazing land by examining global improvements in output per hectare of grazing land based on FAO (2017a) data. We focused on the last 30 years for this trend line in part because knowledge of use of crops before this time is particularly uncertain. This calculation is necessarily imperfect as there were large, but un- known, switches in the quality of grazing land since 1962, and some of the gains were due to these switches rather than to improved management of each hectare of grazing land. However, it leads us to project a 27% rate of increase in forage consumed per hectare of grazing land.

78. Rojas-Downing et al. (2017).

79. AnimalChange (2012), Figure 7. This analysis focused on efficiencies based on protein (kilograms of protein in output, e.g., meat, divided by kilograms of protein in feed). This analysis also noted that feed conversion efficiencies were not widely different in different regions for the reasons we discuss related to backyard systems.

80. Lamb et al. (2016).

81. Erb et al. (2009).

82. Shields and Orme-Evans (2015).
83. GlobAgri-WRR results counting emissions from enteric methane, manure management, and emissions from pasture and paddocks. FAO's GLEAM model estimates ruminant emissions at 80% of global emissions from livestock, although the calculations are not directly comparable because the GLEAM estimate incorporates not only these emissions but also emissions associated with feed production and some postfarm energy and a particular form of land-use change. Gerber et al. (2013), 16, Figure 2.

84. FAO does not directly track or estimate the percentage of feed grains that are provided to different animal types. Herrero et al. (2013) estimated that in 2000, 78% of feed grains were fed to pigs and poultry, with the remainder for ruminants.

85. Herrero et al. (2013), Figure 5. Diagram C shows the emissions per kilogram of milk and the relationship to the digestible portion of the feed in megajoules per kilogram, and Diagram D shows the same for beef. As feed quality improves, there are disproportionate reductions in emissions intensity.

86. The quantity of methane a ruminant will produce from each kilogram of feed will generally be lower for higher-quality feeds, but this relationship turns out to be more complex than previously thought and varies by type of feed and quantities consumed. In contrast, the more digestible the feed, the more meat or milk a ruminant will produce from each kilogram. Because the methane produced for each kilogram of feed declines as digestibility increases, fewer GHG emissions are produced for each kilogram of milk or meat.

87. McDermott et al. (2011), Tables 2 and 3; Pica-Ciamarra et al. (2011).

88. FAO (n.d.); Punjabi (2008).

89. Punjabi (n.d.).

90. Alexandratos and Bruinsma (2012), 132.

91. Wirsenius et al. (2010), Table 4.

92. Herrero et al. (2013), Figure 4. Systems are defined in this paper, and in the so-called Seres-Steinfeld system, by whether they are grazing only, mixed systems of grazing and feeds (a broad category that varies from only 10% feed to 90% feed), or entirely feed-based, and whether they are in arid, temperate, or humid zones.

93. Herrero et al. (2013), Figure S47.

94. Gerber et al. (2010).

95. Gerber et al. (2010).

96. d'Alexis et al. (2012); d'Alexis et al (2013a); d'Alexis et al. (2013b).

97. This analysis appears in Herrero et al. (2013).

98. Gerber et al. (2010), 35, 71.

99. Vellinga and Hoving (2011).

100. Calculated from files provided for the year 2000 as back up materials to Herrero et al. (2013). Beef is 16 percent and dairy is 19 percent.

101. Blummel et al. (2008); Blummel et al. (2009).

102. Thornton and Herrero (2010).

103. Walli (2011).

104. Cardoso et al. (2016).

105. Gerber et al. (2013).

106. Murgueitio et al. (2011); Chara (2012).

107. Murgueitio et. al. (2011).

108. Calle et al. (2013).

109. Calle et al. (2013).

110. Riguero-Rodriguez (2005); Solorio et al. (2016).

111. Cardoso et al. (2016).

112. Boddey et al. (2004); Braz et al. (2013).

113. Cardoso et al. (2016). A separate study, de Figueiredo et al. (2016), found even larger production increases and GHG savings from similar improvements but did not evaluate animals on a "herd basis," which includes both unproductive and productive cows.

114. Gerber et al. (2010), 71. Calculations on a herd basis are lower than calculations that focus only on the milk-producing cow because they count milk-producing cows when they are not lactating, plus all young animals. Comparisons on a herd basis are more meaningful because one way dairy becomes more efficient is by increasing the percentage of cows in the total herd that are producing milk. This can be done by increasing fertility rates, reducing mortality, and reducing the time between lactations of milk-producing cows.

115. Ooko (2014).

116. Bryan et al. (2011).

117. Orodho (2006).

118. Place et al. (2009).

119. Hassanali et al. (2008).

120. Herrero et al. (2011).

121. Thornton and Herrero (2010).

122. GlobAgri-WRR model.

123. Strassburg (2012) estimated that roughly one-third of the potentially improvable grazing land in Brazil was in native vegetation that should not be improved.
124. Authors' calculations.

125. Dixon and Coates (2009); Decruyenaere et al. (2009); Swain et al. (2011).

126. Boval and Dixon (2012); Boval et al. (2007); Fanchone et al. (2012).

127. See the discussion of economic findings by Embrapa studies in Searchinger and Amaral (2009).

128. Rueda et al. (2003).

129. Strassburg (2012).

130. Cohn et al. (2014).

131. Barona et al. (2010). The increase in cattle per hectare was roughly 50%.

132. Herrero and Thornton (2013); IFAD (2009); Department of Agriculture, Forestry, and Fisheries (2012).

133. To cite just two study examples, Cohn et al. (2014) and Henderson et al. (2016) found strong linkages between transportation time and market access and levels of intensification in livestock production in Brazil and sub-Saharan Africa, respectively.

134. Evenson (2003a); Tischer et al. (2014).

135. Alexandratos and Bruinsma (2012); Searchinger, Hanson, Rangana-than, et al. (2013); Foley et al. (2011).

136. Atlin et al. (2017).

137. Atlin et al. (2017).

138. O'Connor et al. (2013).

139. Prigge et al. (2012).

140. Access to Seeds Foundation (n.d.).

141. Hall and Richards (2012).

142. Hall and Richards (2012); Jannink and Lorenz (2010); Nakaya and Isobe (2012).

143. Shimelis (2012).

144. Information about the IRRI monsoon-resistant rice variety was gathered from Higgins (2014).

145. National Human Genome Research Institute (2015).

146. Chen and Rajewsky (2007).

147. Griffiths et al. (2000); Primrose (1995).

148. Personal communication with Gary Atlin, program officer, Bill and Melinda Gates Foundation (June 2017). Periodic announcements are also made in the press by various seed companies; e.g., "NRGene and Syngenta Expand Genomics Collaboration in Key Crops," https://www.businesswire.com/news/home/20190110005053/en/NRGene-Syngenta-Expand-Genomics-Collaboration-Key-Crops.

149. Varshney et al. (2012).

150. Varshney et al. (2012).

151. Varshney et al. (2012).

152. Naylor et al. (2004) use the word orphan to describe crops that "receive little scientific focus or funding relative to their importance for food security in the world's poorest regions." They use minor to describe crops other than the major food crops of wheat, rice, maize, and soybeans. However, Varshney et al. (2012) associate the word orphan with both the extent of research and commercial value. They write, "As they are not extensively traded and receive little attention from researchers compared to the main crops, these important crops for marginal environments of Africa, Asia and South America are often referred to as 'orphan crops.'"

153. Nelson et al. (2014).

154. CFS (2014).

155. Editors of Nature (2013); FAO (2012b).

156. NRC (2004).

157. Snell et al. (2012).

158. Greenpeace International has long been a leading opponent of genetic engineering. Its website expresses concerns about the potential consequences of genetic engineering on human health but cites no claims of actual harm to human health to date from an engineered crop. See http://www.greenpeace.org/international/en/campaigns/agriculture/problem/genetic-engineering/failings-of-ge/.

159. The evidence is summarized in NAS (2016).

160. Séralini et al. (2011).

161. Séralini et al. (2014).

162. NAS (2016).

163. Myers et al. (2016) provide a thorough summary of evidence from all sources of potential effects on human health.

164. Zhang et al. (2019).

165. de Souza et al. (2017).

166. NRC (2010).

167. Krishna and Qaim (2012).
168. Wang et al. (2009) found large reductions in the use of pesticides in China despite occasional problems with increased growth of secondary insects. A later article also found reductions, but smaller (Zhao et al. 2011). Other evidence showed an increase in beneficial predators in fields that used Bt cotton (Lu et al. 2012).

169. NAS (2016).

170. NAS (2016).

171. Porterfield (2017).

172. Visser (2018).

173. Tabashnik and Carrière (2017).

174. NRC (2010).

175. Tabashnik and Carrière (2017).

176. NAS (2016).

177. Schütte et al. (2017).

178. Tabashnik and Carrière (2017); NAS (2016).

179. Benbrook (2016), supplemental tables worksheet S1.

180. Benbrook (2016), supplemental tables worksheet S2, S3.

181. Myers et al. (2016).

182. Hoopman et al. (2018).

183. NRC (2010).

184. E.g., Shi et al. (2011).

185. Stone (2012) provides a summary of the wide volume of literature on the yield effects of Bt cotton in India, and Smale et al. (2009) provide summaries of the literature on the broader economics, including yield, of Bt crops in many developing countries.

186. Sexton and Zilberman (2011) provide an example of the challenge. They found enormous yield gains through GM crops by regressing the yield growth in countries that have broadly adopted GM crops against that in countries that have not. Yet countries that have adopted these crops, such as Brazil, Argentina, China, and the United States, have also made other large investments in agriculture, so it is difficult to segregate the consequences of GM crops.

187. NRC (2010); NAS (2016), 127–33.

188. NRC (2010).

189. Fernandez-Cornejo and Wechsler (2012).

190. NAS (2016).

191. NAS (2016), 15.

192. NAS (2016), 111–14.

193. Stone (2012).

194. Gruere and Sun (2012).

195. Supporting this judgment that Bt cotton has boosted yields is the fact that studies that have tried to control for selection bias or use methods that should not reflect selection bias still find significant yield gains despite finding higher benefits from management changes (Crost et al. 2007; Kathage and Quaim 2012; Gruere and Sun 2012), and the fact that the overwhelming majority of peer-reviewed studies, biased or not, do find yield gains.

196. NAS (2016).

197. NAS (2016).

198. Kathage and Quaim (2012); Smale et al. (2009).

199. NAS (2016).

200. Wiggins (2009) provides a good summary of the debate about the productivity and advantages and disadvantages of small versus larger farms in developing countries.

201. Tefera et al. (2016).

202. NRC (2004); NRC (2010); EU Joint Research Centre (2008); AMA (2012); AAAS (2012); NAS (2016).

203. NAS (2016).

204. Ronald (2011) gives an example.

205. NRC (2004).

206. Gonsalves et al. (2007).

207. Davidson (2007); Witty et al. (2013).

208. McGrath (2014).

209. Descriptions of the potato story and the other crop advances described in this paragraph can be found on the website of the 2Blades Foundation, 2blades.org (accessed March 2019).

210. 2blades.org.

211. http://2blades.org/projects-and-technology/projects/resistance-to-bacterial-diseases-in-tomato/.

212. Strange and Scott (2005).

213. Teng and Krupa (1980); Teng (1987); Oerke et al. (1994); Oerke (2006).

214. Jones and Dangl (2006).

215. Jones and Dangl (2006).

216. Jones (2017).
217. NAS (2016).

218. Gepts (2006).

219. Barrangou and Doudna (2016).

220. For a summary, see Ledford (2016).

221. Nelson et al. (2014).

222. The world devoted 2.23 percent of total GDP to R&D in all sectors in 2015 (World Bank 2017e), and a strong case can be made for increas-
ing research funding across all sectors generally (Griffith 2000). By
contrast, world agricultural GDP was $3.62 trillion in 2014 according
to the World Bank (2017f). If agricultural R&D were still $52 billion,
the percentage would be roughly 1.4 percent ($50 / $3,620 = 0.014).
Assuming from partial data described below that it has grown by 20
percent, then this percentage would have grown to 1.7 percent.

223. Beintema et al. (2012).

224. CGIAR (2017).

225. Mukherjee et al. (2018).

226. Nieburg (2013); Motamayor et al. (2013).

227. Jaganathan et al. (2018) describe recent breeding progress in a variety of crops enabled by CRISPR-CAS, and Lemmon et al. (2018) describe how breeders used CRISPR-CAS to make rapid improvements in plant architecture, flower production, and fruit size of groundcherry and tomatoes.

228. See GCP (2014).

229. AOCC partners include Beijing Genomics Institute; Biosciences Eastern and Central Africa; The iPlant Collaborative; Life Technologies; Mars Incorporated; New Partnership for Africa's Development (NEPAD); University of California, Davis; World Wildlife Fund; and World Agroforestry Centre.

230. Howard Shapiro, personal communication, May 15, 2014. Shapiro was a founder of the consortium.

231. FAO (2011b). Preliminary results from the Global Land Degradation Information System (GLADIS) assessment.

232. Place et al. (2013).

233. Cervigni and Morris (2016). By "drylands," we refer to the zones clas-
sified on the basis of an aridity index of 0.05 to 0.65, and encompass-
ing the dry subhumid, semiarid, and arid zones. We are not referring
to the hyperarid zone with an aridity index of less than 0.05 and
which does not support crop and livestock production and is very
sparsely populated. According to recent analysis by the World Bank,
the drylands including these three zones cover some 1.3 billion ha, or
nearly 55% of sub-Saharan Africa, and are home to about 390 million
people, or roughly 48% of the region's population. The dominant
farming systems in the drylands of sub-Saharan Africa are "agro-
pastoral" and "maize mixed."

234. Johnson et al. (2006).

235. Koohafkan and Stewart (2008).

236. Cervigni and Morris (2016).

237. Allison (1973).

238. Stoorvogel et al. (1993); Liu et al. (2010).

239. Powlson et al. (2016).

240. Marenya and Barrett (2009a).

241. Rockström et al. (2003).

242. Bationo et al. (2006). As these authors note, "Soil moisture stress is perhaps the overriding constraint to food production in much of Africa. Moisture stress is not only a function of the low and erratic precipitation but also of the ability of the soil to hold and release moisture. About 10% of the soils in Africa have high to very high available water-holding capacities. . . . Most African soils are inherently low in organic carbon (<20 to 30 mg/kg) and consequently have low capacity to retain soil moisture. . . . The development of conservation agriculture technologies with permanent soil cover will be of importance for the conservation of soil moisture as shown in various FAO projects."

243. Marenya and Barrett (2009b). Several studies are cited in Titonell and Giller (2013).

244. Xie et al. (2007); Yu et al. (2009).

245. WOCAT (2015).

246. Reij et al. (2009); Stevens et al. (2014); Reij and Winterbottom (2015).

247. This information is from work by two researchers from the University of Niamey (Boubacar and Sambo), who undertook a quick study in five villages in the Kantché department (Southern Zinder) to look at regreening and food security. A blog about this work is accessible at http://africa-regreening.blogspot.com/2012_03_01_archive.html.

248. Reij et al. (2005); Botoni and Reij (2009); Reij et al. (2009).

249. Tropical Forages (2012).

250. Tropical Forages (2012).

251. Yamba and Sambo (2012).

252. Rockström et al. (2003).

253. Mekdaschi and Liniger (2013); Critchley and Gowing (2012).

254. Hassane et al. (2000).

255. Sawadogo (2006).
256. Hassane et al. (2000) show that yield improvements from water harvesting can vary from 500 to 1,000 kg/ha, depending on other factors such as soil fertility. Sawadogo (2013) found that farms in Burkina Faso using water harvesting techniques increased yields 50-100% when compared with adjacent cultivated land not using harvesting techniques. An increasing number of farmers in the Sahel have used water harvesting techniques to reclaim lands that had been out of production for generations. In areas close to Tahoua, Niger, they were able to convert very low potential lands into productive lands (as measured not only by yields but by land prices). Mazvimavi et al. (2008) found that water harvesting, combined with conservation agriculture, increased yields per hectare by 50% on average across nine districts in Zimbabwe.

257. Doumbia (2010).

258. Doumbia (2010); Feed the Future (2012).

259. Hayashi et al. (2008); Tabo et al. (2007); Sanginga and Woomer (2009); ICRISAT (2009).

260. Aune and Bationo (2008); Vanlauwe et al. (2010).

261. Sawadogo (2013).

262. Sanders and Ouendeba (2012).

263. FAO (2012b).

264. Williams and Fritschel (2012); Bunderson (2012); Pretty et al. (2006); Branca et al. (2011).

265. According to IFDC (2011), in West Africa, the adoption of integrated soil fertility management practices by farmers on 236,200 ha between 2006 and 2010 resulted in yield increases for cassava, cowpeas, groundnuts, and maize—including a 58% yield increase for groundnuts, as well as revenue increases of 179% for maize and slightly more than 50% for cassava and cowpeas.

266. Arslan et al. (2013); Arslan et al. (2014). "Conservation Farming package as promoted in Zambia consists of following practices: (1) reduced tillage on no more than 15% of the field area without soil inversion, (2) precise digging of permanent planting basins or ripping of soil with a *Magoye ripper* (the latter where draft animals are available), (3) leaving of crop residues on the field (no burning), (4) rotation of cereals with legumes and (5) dry season land preparation."

267. Arslan et al. (2013).

268. Arslan et al. (2015) provides a good summary of these studies.

269. Arslan et al. (2014). An endogeneity problem is one in which a study is unable to distinguish statistically which of two related factors is cause and which effect, or to which degree, or whether both are the result of a third factor.

270. Arslan et al. (2015).

271. Giller et al. (2015).

272. Giller et al. (2015).

273. Beebe (n.d.).

274. Duncan et al. (2016).

275. Powlson et al. (2016).

276. Liniger et al. (2011).

277. Mafongoya (2006).

278. Mafongoya (2006).

279. Marenya and Barrett (2009a).

280. Giller et al. (2015); Williams and Fritschel (2012); Bationo et al. (2007).

281. Liang et al. (2006); Lehmann (2007); Whitman and Lehmann (2009).

282. W4RA (2017).

283. Reij and Garrity (2016).

284. Reij and Winterbottom (2015).

285. FAO (2019a).

286. Modeling using the GAEZ model accessible at http://webarchive.iiasa.ac.at/Research/LUC/GAEZ/results/5_7.htm.

287. Table 4.9 of Alexandratos and Bruinsma (2012) provides cropping intensities in 2006-7 for rainfed and irrigated land separately. Assuming that all irrigated lands are harvested at least every year, around 70 Mha of irrigated land are double-cropped. According to Siebert et al. (2010), 150 Mha are double-cropped in total. Putting these two estimates together, approximately 80 Mha of rainfed land are double-cropped, which according to Table 4.9 is 6% of the 1,335 Mha of rainfed cropland as of 2006-7.

288. Kalaiselvi and Sundar (2011).

289. Shiao et al. (2015). Chapter 28 on rice cultivation discusses declining groundwater in Tamil Nadu and Punjab in more detail.

290. Heinimann et al. (2017).

291. Alexandratos and Bruinsma (2012), Table 4.9.

292. As summarized in Ray and Foley (2013), FAOSTAT data suggest an increase in harvested area of 12.1 Mha per year between 2000 and 2001, and an increase in cropland area of only 2.9 Mha per year during that period, for a difference of 9.2 Mha "saved" per year, which over 11 years, implies 101 Mha of additional harvested area without expansion of cropland.

293. Ray and Foley (2013).
294. To develop an estimate of fallow land, we deduct 80 Mha of cropland from the total estimate of rainfed cropland in Table 4.9 in Alexandratsos and Bruinsma (2012) to come up with land that is not double-cropped, and deduct 160 Mha of land from harvested area (reflecting two crops per year on 80 ha of land). The resulting difference between single-cropped cropland and harvested area suggests around 350 Mha of fallow land each year. FAO (2017a) indicates a 251 million hectare difference between total arable land (including land devoted to permanent crops such as trees) and harvested area in 2009. These figures differ somewhat from the 299 Mha presented in Alexandratsos and Bruinsma (2012), which adjusted arable land and harvested land in a couple of ways. However, assuming that roughly 150 Mha were double-cropped for reasons discussed above, that means 400 Mha were not harvested at all.

295. For example, FAO reported 158 Mha of U.S. cropland in 2012 (FAO 2019a). However, in 2012 (the most recent year for which USDA is reporting data), it reported 138 Mha of U.S. cropland including planted areas that could not be harvested and summer fallow areas (USDA/ERS 2017). The roughly 20 Mha difference consists roughly equally of two land categories: idled cropland, which is primarily Conservation Reserve Program lands, and cropland used for pasture.

296. Nefedova (2011); Ioffe (2005); Kuemmerle et al. (2010); Kurganova et al. (2007). FAO data for 2009 categorize 44% of arable land in the former Soviet Union as unharvested. The region abandoned croplands in vast numbers after the fall of the Soviet Union, and this figure suggests that it includes some or much of that land. But this land has been reforesting and otherwise sequestering carbon.

297. Kurganova et al. (2010).

298. Good et al. (2016).

299. Pires et al. (2016).

300. Relative to 1986–2005. Collins et al. (2013).

301. Easterling et al. (2007).

302. Porter et al. (2014).

303. Craparo et al. (2015); Eitzinger et al. (2011); Ortiz et al. (2008); Teixeira et al. (2013).

304. For increasing scientific evidence of the role of direct heat stress on crops, see Asseng et al. (2011), Lobell et al. (2012), and Shah et al. (2011).

305. IPCC (2014); Semenov et al. (2012); Teixeira et al. (2013).

306. As just one example, Giannini et al. (2017) project a 13% decline in availability of pollinators by 2050 in Brazil.

307. Zhou et al. (1995).

308. Harrington et al. (2007).

309. Lobell and Field (2007).

310. Jones and Thornton (2013).

311. For evidence of adverse impacts of climate change on crops and the disruptive consequences of more likely extreme events, see Battisti and Naylor (2009); Lobell and Field (2007); Schlenker and Roberts (2009). For increased evidence of likely adverse effects in Africa, see Schlenker and Lobell (2010). For recent assessments suggesting the more likely adverse consequences of climate change in colder regions, see Semenov et al. (2012).

312. World Bank (2014).

313. Lesk et al. (2016).

314. Dale et al. (2017).

315. World Bank (2014).

316. Porter et al. (2014).

317. Liu, Xu, Zhuang, et al. (2013).

318. Leakey et al. (2009).

319. Long et al. (2006).

320. World Bank (2014).

321. Schlenker and Roberts (2009).

322. Liang et al. (2017).

323. Craparo et al. (2015); Peng et al. (2004); Rao et al. (2014).

324. Lobell et al. (2011).

325. World Bank (2014); Lobell et al. (2008).

326. IPCC (2014).

327. Nelson et al. (2009), as cited in IPCC (2014).

328. Laderach et al. (2010); Eitzinger et al. (2011); Bunn et al. (2015).

329. Bunn et al. (2015).

330. Jones and Thornton (2015).

331. Porter et al. (2014).

332. Porter et al. (2014), summarizing Hertel et al. (2010); Calzadilla et al. (2013); Lobell et al. (2013); and Nelson et al. (2013).

333. Nelson et al. (2009).

334. Lloyd et al. (2011).
335. Hewitson and Crane (2006).

336. Vermeulen et al. (2013).

337. Gershunov and Barnett (1998).

338. Estes et al. (2013).

339. Thornton et al. (2011).

340. Sherman et al. (2016).

341. Dore (2005); Wetherald and Manabe (2002).

342. For example, this is the irrigation focus of Sri Lanka's climate strategy; Vermeulen et al. (2013).

343. Xie et al. (2014).

344. Thornton and Cramer (2012); Lobell et al. (2011).

345. Watts (2016).

346. Urban et al. (2012).

347. Bolaños and Edmeades (1996); Cooper et al. (2014); World Coffee Research (2015).

348. Kopp et al. (2017); DeConto and Pollard (2016).

349. Dasgupta et al. (2009).

350. Islam et al. (2015).

351. Renaud et al. (2015).

352. Islam et al. (2015).

353. Renaud et al. (2015).

354. Jones and Thornton (2009).

355. We do not show these higher yield gains as reducing the food (crop calorie) gap because we assume that the alternative to these higher yield gains would be "baseline" levels of yield gain that would result in the same number of crop calories produced, but with additional expansion of agricultural land. Our food gap closure menu items therefore focus on the demand-reduction techniques in Course 1, which by limiting the gap can reduce the amount of additional food production necessary between 2010 and 2050 and increase the likelihood that the land and GHG mitigation gaps can be closed while adequately feeding everyone in 2050.

356. This global 15% decline in crop yields (actually an average decline of 15.48%) is drawn from the LPJmL scenario without CO₂ fertilization described in Müller and Robertson (2014).

357. GlobAgri-WRR model. If crop yields were equal across crops, purely reducing yields from 1.48 (a 48% growth above 2010 levels) by 15.48% would lead to 25% growth above 2010 levels (1.48 * 0.8452 = 1.25). Because all crops have different yields, and there are varying amounts of each crop grown in the world, the actual overall growth (across all crops) ends up being 28%, as calculated by GlobAgri-WRR.

358. GlobAgri-WRR model. Asia (outside of China and India) is next at "only" 35 Mha of cropland expansion between 2010 and 2050 under our baseline scenario.

## REFERENCES

To find the References list, see page 500, or download here: www.SustainableFoodFuture.org.

## PHOTO CREDITS

Pg. 144 Ollivier Girard/CIFOR, pg. 146 Neil Palmer/CIAT, pg. 150 Hari Priyadi/CIFOR, pg. 151 Lynn Ketchum/Oregon State University, pg. 158 Kyle Spradley/ Curators of the University of Missouri, pg. 166 Neil Palmer/CIAT, pg. 178 Neil Palmer/CIAT, pg. 182 Dean Calma/IAEA, pg. 188 Ratclima/Flickr, pg. 194 Luciana Gallardo Lomeli, World Resources Institute, pg. 202 Luis Solarte/CIPAV, pg. 204 Wiley Brooks-Joiner/Flickr, pg. 208 Lance Cheung/USDA, pg. 211 CDKNetwork/Flickr, pg. 220 CIMMYT.
<figure><img src="image_120.png" /></figure>
COURSE 3

# Protect and Restore Natural Ecosystems and Limit Agricultural Land-Shifting

Increasing agricultural productivity and reducing the rate of growth in demand for agricultural products permit greater protection of ecosystems and their stored carbon. But these strategies alone are not sufficient.

Course 3 focuses on the land management that needs to complement these efforts. One guiding principle is the need to make land-use decisions that enhance efficiency of both agriculture and ecosystem services.

Another is the need to explicitly link efforts to boost agricultural yields with the protection of forests and other natural lands.

## TABLE OF CONTENTS

Chapter 17. The Causes and Consequences of Agricultural Land-Shifting.................................................. 239

Chapter 18. Menu Item: Link Productivity Gains with Protection of Natural Ecosystems .................... 249

Chapter 19. Menu Item: Limit Inevitable Cropland Expansion to Lands with Low Environmental Opportunity Costs .................................................................................................................. 259

Chapter 20. Menu Item: Reforest Abandoned, Unproductive, and Liberated Agricultural Lands .................... 265

Chapter 21. Menu Item: Conserve and Restore Peatlands.................................................................................. 273
Introduction

Holding down growth in food demand (Course 1) and boosting agricultural yields (Course 2) could prevent expansion of the net global area of agricultural land. In the case of our more ambitious scenarios, these two strategies could even lead to a decline in agricultural land area. But our calculations are based on the net need for agricultural land. Our model assumes that every hectare of land that is not converted because of reduced growth in demand (or increased yields on existing hectares) saves the carbon that would otherwise be released by converting that additional hectare. Unfortunately, the land-use challenge is more complicated than that. Even if net expansion of agriculture is eliminated, agricultural production will continue to shift from one place to another. These shifts often involve conversion of biologically diverse and carbon-rich habitats, which immediately releases long-stored carbon and harms biodiversity.

Although necessary to hold down net expansion of
agricultural land, yield growth for some crops in
tropical countries could even accelerate these shifts,
by making farming more profitable and giving
farmers an incentive to clear new land. Translat-
ing yield gains into full benefits in the real world
therefore requires land management efforts that are
designed to minimize gross—not just net—agricul-
tural expansion and reduce the environmental costs
of any expansion that does occur.

To achieve climate and ecosystem goals, some
active restoration efforts are also required. Agri-
cultural land that is abandoned—whether as a
result of agriculture shifting to other locations or
net declines in agricultural land area—tends to
naturally regenerate into forests and other native
habitats. However, active restoration could enhance
benefits for carbon storage and other ecosystem
services. Today, a limited amount of agricultural
land is so marginal that it is incapable of generating
higher yields in practice and warrants restoration
right away. Little-used drained peatlands release so
much carbon dioxide that they also deserve priority
action.
<figure><img src="image_121.png" /></figure>
<figure><img src="image_122.png" /></figure>

<figure><img src="image_123.png" /></figure>

<figure><img src="image_124.png" /></figure>
# THE CAUSES AND CONSEQUENCES OF AGRICULTURAL LAND-SHIFTING

Agricultural land is not only expanding overall but also shifting its locations among and within regions and countries, which imposes environmental costs. This shifting is not to be confused with what is sometimes called "shifting" or "swidden" agriculture, in which farmers with few inputs engage in multiyear crop rotations, allowing exhausted fields to reforest before clearing them again.
## Global and Regional Shifts in Locations of Agricultural Land

At the global level, agriculture is generally shifting from the North toward the South. Between 1961 and 2013, cropland declined by 126 million hectares (Mha) in Europe and North America but expanded by 331 Mha in Africa, Asia, Latin America, and Oceania.¹ As discussed in Chapter 10, pasture area is also shifting, declining by 66 Mha in Australia and New Zealand between 1994 and 2014 while expanding in Latin America.²

This trend is likely to continue because population and demand for food will increase more rapidly in developing countries. For example, using older UN population growth projections, the UN Food and Agriculture Organization (FAO) projected that cropland area would decline by 38 Mha in

developed countries between 2006 and 2050 even as it expands by another 107 Mha in developing countries.³ Using the GlobAgri-WRR model, we also project a shift in the global share of agricultural land. Because future trade is so difficult to estimate, we assume that the percentage of each food imported or exported will remain at the same levels as in 2010, which means the model does not allow a higher percentage of food consumed in developing countries to come from developed countries in the future. Even so, the model estimates that agricultural land will expand by an additional 474 Mha in developing countries but by only 119 Mha in developed countries (Table 17-1).⁴ We believe that even this relatively small role for developed countries may be an overestimate because our baseline scenario probably does not fully capture the effects of increasing land-use competition in developed countries.

<table><caption>Table 17-1 | Projected change in agricultural land use by region, 2010–50 (baseline scenario)</caption><thead><tr><th>REGION</th><th>CHANGE IN CROPLAND AREA (MHA)</th><th>CHANGE IN PASTURELAND AREA (MHA)</th><th>TOTAL CHANGE IN AGRICULTURAL AREA (MHA)</th></tr></thead><tbody><tr><td>Asia (excluding China and India)</td><td>42</td><td>61</td><td>103</td></tr><tr><td>Brazil</td><td>2</td><td>34</td><td>37</td></tr><tr><td>China</td><td>-25</td><td>-1</td><td>-26</td></tr><tr><td>European Union</td><td>-17</td><td>8</td><td>-8</td></tr><tr><td>Former Soviet Union</td><td>0</td><td>-33</td><td>-33</td></tr><tr><td>India</td><td>32</td><td>2</td><td>34</td></tr><tr><td>Latin America (excluding Brazil)</td><td>12</td><td>68</td><td>80</td></tr><tr><td>Middle East and North Africa</td><td>8</td><td>10</td><td>18</td></tr><tr><td>OECD (other)</td><td>5</td><td>52</td><td>57</td></tr><tr><td>Sub-Saharan Africa</td><td>104</td><td>158</td><td>262</td></tr><tr><td>United States and Canada</td><td>27</td><td>43</td><td>70</td></tr><tr><td><strong>Total</strong></td><td><strong>192</strong></td><td><strong>401</strong></td><td><strong>593</strong></td></tr></tbody></table>

Note: Figures may not sum correctly due to rounding.

Source: GlobAgri-WRR model.
## Gross versus net agricultural expansion

Many years of satellite image studies show that locations of agricultural land also shift substantially within regions.⁵ Figure 17-1 shows an analysis by FAO based on satellite imagery of forest losses and gains by continent from 1990 to 2005. Although both Africa and South America had net losses of forest, these were substantially smaller than gross losses, which implies that agricultural land expansion in some places is outpacing reversion to forests on abandoned agricultural land elsewhere.⁶ Asia, too, had large gross losses, particularly of native wet tropical forests. The continent experienced a net forest gain overall (nearly 50 Mha between 1990 and 2010), but this gain was largely due to establishment of tree plantations, particularly in China.⁷

A separate study of deforestation in Latin America from 2001 to 2010 found that gross forest loss exceeded net forest loss by three to one (Figure 17-2). In the United States, 3 Mha were converted to cropland between 2008 and 2012, even as 1.8 Mha of cropland elsewhere in the country were abandoned or otherwise taken out of food production.⁸ In Europe, one study found 1.6 Mha of agricultural expansion from 1990 to 2006, but 2.1 Mha of other agricultural land reverted to some kind of forest or other more natural vegetation.⁹

Although these shifts in the locations of agriculture permit some abandoned lands to regenerate, the trade-off tends to be poor from the perspective of biodiversity and carbon storage. New cropland is being established primarily in the tropics and subtropics, where biodiversity is much higher.¹⁰ Many newly converted lands were formerly natural or relatively natural forests and grasslands,¹¹ whose biodiversity is often irreplaceable.¹²

Because conversion in the tropics often occurs on relatively intact native ecosystems, the carbon losses are often higher per hectare than conversion of agriculture in other parts of the world. It is at least as important to note that tropical yields also tend to be lower. As a result, the carbon storage lost per ton of crops produced is higher in the tropics than in the temperate and boreal zones.¹³ Time also matters. The losses of carbon during land conversion mostly occur immediately, while restoring carbon in vegetation and soils occurs gradually over longer time periods.¹⁴

In addition, farmers tend to abandon land that is dry and at higher elevations, whereas they tend to clear wetter and more productive ecosystems, which tend to be richer in carbon and biodiversity.¹⁵ Overall, gross land conversion caused by shifting locations of agricultural land presents a major environmental challenge that has received insufficient global attention.

<figure><img src="image_125.png" /><figcaption>Figure 17-1 | Gross forest losses are far greater than net forest losses because locations of agricultural lands are shifting</figcaption></figure>

Source: FAO (2012a).
<figure><img src="image_126.png" /><figcaption>**Figure 17-2** | While forests recovered in some areas of Latin America from 2001 to 2010, even larger areas were cleared elsewhere for agriculture</figcaption></figure>

Source: Aide et al. (2012).
## Drivers of Agricultural Land Expansion and Location Shifting

Several powerful forces are driving shifts in location of agricultural land, and they are likely to continue pushing expansion in many locations even if the total, global demand for agricultural land stabilizes. One important driver is high growth in demand for food in specific regions. Another is rising demand for specific food types that are best grown in the tropics. A third is the advance of roads and other infrastructure across the global South that is opening up new, financially cheap but environmentally expensive lands for agriculture.

### Some regions face high growth in demand for food

In some countries or regions, the growth in food demand is likely to be so great that it will prove extremely difficult, if not impossible, to prevent some expansion of agricultural area.

Sub-Saharan Africa poses the greatest challenge, as explored in Box 2-4, because the likely growth in domestic food demand will make some expansion of agricultural land inevitable. Although we use FAO's predictions of robust yield growth in the region of roughly 250 percent between 2006 and 2050,¹⁶ our baseline projection is that the region's cropland will nevertheless still expand between 2010 and 2050 by roughly 100 Mha. If we use less optimistic yield trends based on 1989–2008 rates—our “alternative baseline”—we project cropland expansion of 241 Mha.¹⁷ These projections assume that the region continues to rely heavily on other countries for its staple foods, importing roughly 20 percent of meat and milk and 18 percent of cereals.¹⁸

Other analyses come to similar conclusions. One study found that even if countries in West Africa were able to more than double their rates of cereal yield gain between 2001 and 2014 (and triple their rates of maize yield growth) out to 2050, their imports of cereals would still have to grow from 21 percent to 45 percent by midcentury if they did not expand their cropland.¹⁹ Actual self-sufficiency in maize would require yield growth of roughly 144 kilograms (kg) per hectare per year, which is five times the rates of yield gain from 2001 to 2014 in Africa and roughly 3.5 times the global average rate of yield growth. Some estimates indicate that for

sub-Saharan Africa to become self-sufficient in crop calories, cereal yields would have to increase four-fold between 2007 and 2050. Using FAO 2050 yield estimates, crop area would have to grow by 140 Mha from 2006 to 2050 just to maintain roughly present levels of imports.²⁰

### Some regions will meet high international growth in demand for vegetable oil and animal feeds

The growing demand for vegetable oil and high-protein animal feeds, and the ability of tropical and subtropical countries to meet this demand well by producing palm oil and soybeans, represents another driver of gross land expansion in some countries and a likely shift of agricultural production to their lands.

Soybeans are inputs to both vegetable oils and animal feeds. Globally, soybeans were grown on 84 Mha in 2003 and 111 Mha in 2013,²¹ a 33 percent increase over one decade despite advances in breeding and management of this heavily researched commodity crop. Other researchers have projected that even with yield gains, the global area dedicated to soybeans will need to increase by another 30 Mha by 2050 or even by 2030 to meet estimated demand.²² Latin America is a good region for growing soybeans, with Brazil and Argentina already being two of the world's three principal producers. Even in Africa, where soybean yields to date have been low, vast areas have relatively high growth potential.²³ The economics of rising demand, relatively lower land costs in emerging and developing countries, and good yield potential will continue to drive expansion of soybean planting in these areas.

Continued growth in demand for palm oil will also place enormous pressures on tropical rain forests, which provide the best conditions for growing oil palm trees. With an average global yield of 3.7 tons of oil per hectare, oil palm generates seven times the oil yield per hectare of soybeans.²⁴ In 2015, oil palm provided 31 percent of the world's vegetable oil production by tonnage, even beating out soybeans (at 24 percent) as the world's dominant vegetable oil crop.²⁵ The 13 Mha of oil palm plantations around the world in 2011²⁶ are heavily concentrated in Indonesia and Malaysia, which together accounted for 85 percent of global palm oil supply in 2015.²⁷ But the industry is making inroads into West Africa, Central Africa, and South America.²⁸ Despite
some efforts to curtail the use of palm oil,²⁹ experts predict that palm oil will meet an even larger share of future vegetable oil demand because of its high productivity and low cost. One estimate projects a need for at least an additional 12 Mha of oil palm plantations globally from 2009 through 2050 to meet worldwide demand—and potentially more.³⁰ And if palm oil production does not expand but vegetable oil demand continues to grow as projected, even more hectares of land would be converted to grow lower-yielding vegetable crops to meet projected demand.

## The global South is developing its roads and other infrastructure

Agriculture is also expanding in many areas because of new roadbuilding. Studies have shown that new or improved roads into forests typically lead to large areas of deforestation and agriculture expansion along those roads.³¹ In the Brazilian Amazon, for example, 95 percent of deforestation has occurred within 5.5 kilometers (km) of a road.³² Not only do roads provide economic access to new areas but, over time, economic activity starts to grow, especially extractive and agricultural activities. Vested interests in further clearing and roadbuilding emerge. Large roads tend to lead to serial networks of smaller roads.

The environmental effects of roads go beyond direct land-clearing. Roads allow people to hunt wildlife and harvest timber illegally and create paths for invasive species.³³ Vehicles on roads kill large numbers of animals and pose particular problems for species that migrate over large areas.³⁴ Roads also encourage logging.³⁵ New roads are now penetrating many of the world's last remaining forest wildernesses, including the Amazon, Papua New Guinea, Siberia, and the Congo Basin.³⁶

New roads present an enormous challenge to forests and other natural areas because roadbuilding also plays a major role in economic development generally and in the improvement of agriculture on existing croplands and pasture.³⁷ Poor roads increase the costs of inputs, decrease the prices farmers receive for outputs, increase food storage

losses, and create significant additional uncertainties for investors. Many studies have shown that boosting yields of milk and of many crops is often not economical in the absence of good market access, which requires acceptable road networks.³⁸ The rutted, rural roads common in Africa, Latin America, and even much of Asia are therefore major impediments to agricultural improvement.

For these reasons, roads are often built through forests and other natural areas to spur economic development rather than (primarily) to open up new areas for farming. For example, roads may be constructed to connect cities or to increase access to ports: the purpose of a road paved through the Amazon forest from Mato Grosso in the south to Santarém on the Amazon River in the north was to make it less expensive to export soybeans and other crops from Mato Grosso, an already heavily developed agricultural state. But a side effect was to encourage additional deforestation along the road (Figure 17-3).³⁹

Governments have extensive plans for roadbuilding, at different stages of realization, all over the world.⁴⁰ One study has documented 33 new or growing transportation and development corridors in sub-Saharan Africa, extending over 53,000 km. Ten of these roads are active, nine are proposed for upgrading, and 14 are planned.⁴¹ The study found that the transportation networks (including a few railroads) would bisect 408 protected areas and 574 Mha of protected habitats, and that many would “promote serious and largely irreversible environmental change.” Roadbuilding also appears to be getting a boost from international infrastructure funding. The G20 group of wealthy countries committed to double the current value of global infrastructure by 2030 by investing $60–70 trillion worldwide.⁴² The addition of the Asian Infrastructure Investment Bank (AIIB) to the global multilateral bank scene in 2016 is likely to accelerate infrastructural investment. AIIB expects to double its lending within the next five years and to fund major infrastructural projects such as gas pipelines, railways, and motorways.⁴³ Realistically, if roadbuilding follows present plans, large-scale deforestation of intact old-growth forests is all but certain to occur.
<figure><img src="image_127.png" /><figcaption>Figure 17-3 | Roadbuilding has led to deforestation and agricultural expansion in Pará, Brazil</figcaption></figure>

Source: Imagery © 2019 Landsat/Copernicus, Map data © 2019 Google.

## The Potential of Yield Gains to Shift Locations of Agriculture

Because boosting global output per hectare is a mathematically necessary way to meet increases in food demand without land-use change, yield gains are a critical course on our menu. Unfortunately, yield gains can also accelerate shifting and local expansion of agricultural land, particularly in developing countries.⁴⁴ Initial studies struggled to explain this phenomenon and some even suggested that yield gains might increase not just local but even global land use for agriculture. But more recent research has pointed out that expansion occurs at the country level when increased yields lead to greater competitiveness and more exports.⁴⁵ In effect, yield gains do tend to reduce global agricultural land use if compared to the alternative of growth in demand without yield gains—but yield gains can also lead to increased agricultural area where those yield gains occur. It is important to appreciate why.

## The "consumption rebound" effect?

One potential explanation is that boosting yields helps lower prices, and people respond by consuming more food—a consumption “rebound effect.” If consumption increases by a larger percentage than yields, agriculture will expand into new lands. We consider this consumption effect to be generally a small and inappropriate concern.

First, the economic evidence is strong that, on balance, global yield gains will save land. For most foods, people only modestly increase their consumption of crops when prices decline.⁴⁶ As a result, a 1 percent decrease in price will generally cause substantially less than a 1 percent increase in consumption of crops. In addition, a 1 percent increase in crop yield by itself will cause less than a 1 percent decrease in crop price because land is only one cost of production and decreasing land cost by 1 percent does not decrease total costs by 1 percent. In addition, farmers may achieve higher yields by increasing other inputs, and therefore increasing their costs.⁴⁷ Putting these two effects together, although a 1 percent increase in yield by definition
means a 1 percent decrease in land area to produce
the same amount of food, it will in general cause
less than a 1 percent increase in consumption and
will therefore save land overall.

Second, a sustainable food future requires improv-
ing food availability for billions of poor people who
spend large percentages of their income on food.
Lower food prices help to meet their needs, and
intentionally seeking higher prices than necessary
is not morally acceptable. An alternative past with
no Green Revolution would have included more
hunger and less food consumption.⁴⁸ Increasing
the capacity of the poor to consume food, in part by
keeping food prices low, is one of the requirements
for a sustainable food future.

Such an approach does not preclude use of prices
to influence overconsumption by the wealthy,
but that influence must occur through taxes. The
consumption of the world's wealthy people is little
affected by farmgate food prices for two reasons:
price increases have less effect on their consump-
tion, and farmgate prices are a small component of

the retail food prices that people pay in developed
countries.⁴⁹ Increases in farmgate food prices would
therefore mainly affect the poor, and the only prac-
tical way to use prices to target consumption by the
rich is through taxes at the retail level.

One exception may be yield gains for beef and other ruminant meats. These yield increases may not increase total food or total meat consumption, but they may cause consumers to consume more beef and less chicken or vegetable sources of protein. These dietary shifts would not benefit nutrition or the poor but would increase land-use demands and greenhouse gas (GHG) emissions. Studies also estimate that prices have a substantially larger effect on meat consumption than on other foods (sometimes with absolute elasticity values around 1, which means that a 10 percent decrease in price would result in a 10 percent increase in consumption).⁵⁰ Yield increases therefore do have some realistic potential to increase beef consumption. Increases in pasture yields still play a critical role in our menu for a sustainable food future, and it is hard to imagine a future scenario that freezes agricultural

<figure><img src="image_128.png" /></figure>
land expansion without achieving vast increases
in pasture yields. But if higher yields lead to lower
prices, some compensating measures to avoid
increased consumption of ruminant meat may also
be necessary.

The "local production rebound" effect

The more important and environmentally challeng-
ing problem is what can be called a local production
rebound effect.⁵¹ Yield gains—even if they spare
land globally—may encourage local conversion of
forests, savannas, and other natural ecosystems by
lowering local production costs. In other words,
yield gains can improve the economics of farming
per hectare, giving farmers incentives to put more
hectares into production to increase their total
profit. This pattern likely underpins expansion of
soybeans, maize, and beef in Brazil and Argentina,
and of oil palm in Indonesia and Malaysia.

This kind of locational shifting of agricultural
lands does not occur because of yield gains per se.
If all countries increased their yields in a way that
lowered production costs by the same amount, no
country would gain a competitive advantage.⁵² The
shifting occurs when yields increase and production
costs decrease in some countries more quickly than
in others. Countries where yields grow and costs
decline more will be able to produce and export
crops or livestock at lower prices and might there-
fore expand the land area dedicated to those com-
modities to meet increased internal and external
demand.

This challenge does not mean that yield gains
should be avoided because they risk encouraging
local production rebound effects. In general, yield
gains in North America and Europe are unlikely
to trigger regional expansion of agricultural land
because cropland area has been in long-term
decline in these regions due to yield gains and
stabilizing populations. If yield gains improve
these regions' competitive advantage, that is likely
to result only in maintaining more cropland in

production. Even so, breeding that enables crops
to grow in different locations can still cause land
shifting in these regions; for example, breeding
and development of crop varieties that can grow
in drier, shorter growing seasons is likely a con-
tributor to grassland conversion in the U.S. Great
Plains.⁵³

Failing to implement measures to boost yields
in developing countries would be both morally
unacceptable and foolish. It would be morally
unacceptable because it would leave too many
people dependent on farming at a disadvantage, and
because relying on food imports is a risky strategy
for poor countries.⁵⁴ It would also be foolish, in part,
because not all drivers of yield gains will reduce
costs of production and encourage local expansion.
For example, protecting forests will force farmers to
focus more on boosting yields through greater use
of labor or technical inputs and will increase rather
than decrease costs. More fundamentally, without
yield gains poor countries with growing food demand
are all but certain to expand their agricultural lands.
Unless they increase yields, as African experience has
shown, they will expand agricultural land area.⁵⁵ In
addition, if no countries increase their yields, massive
expansion of agricultural land is inevitable. Despite
the risks of locational shifts of some agricultural land,
failing to boost yields is a sure-lose strategy.

The only solution is both to boost yields and to use
government policies where necessary to protect
forests (and other natural ecosystems) and avoid
shifting of locations of agricultural land. Private
sector approaches that try to eliminate deforesta-
tion from their supply chains can also contribute.
Although yield gains can pose risks, the challenge
is to minimize the risks and harness yield gains for
their positive outcomes.
<figure><img src="image_129.png" /></figure>
# MENU ITEM: LINK PRODUCTIVITY GAINS WITH PROTECTION OF NATURAL ECOSYSTEMS

How can the world and farmers achieve the benefits of yield gains while also protecting natural landscapes? The heart of our answer is that efforts to achieve both need to be linked. The two goals of pursuing higher yields and protecting natural landscapes need to be linked by national and local governments, international funders, and private companies.
As part of this linkage, governments also need to develop integrated, spatially explicit, and evolving analytical systems to target roadbuilding and agricultural assistance where it can do the most good and avoid the most harm. This chapter starts by assessing whether governments can protect natural resources and how, then discusses the various methods for linking efforts to improve agricultural productivity with protection of natural landscapes.

## How Governments Can Protect Natural Landscapes

Can governments protect natural landscapes? An extensive literature discusses the various available measures. The core lesson is that landscape protection presents great political and governance challenges but that governments have effective measures available to them to protect natural lands if they can mobilize the political will and master the governance.

### Stop giving away public land for conversion

The most direct measure governments can use to protect natural landscapes from conversion is to stop giving this land away or selling it. The effects can be significant because, in much of the world, governments own the majority of natural land, and conversion occurs only when they grant the right to convert. In Indonesia, for example, the national government claims ownership of nearly all forest (subject to possible claims by Indigenous Peoples as a result of a Constitutional Court ruling).⁵⁶ This land can become available for agricultural development through reclassifications granted by the national forest agency on application by private companies.⁵⁷ By refusing to reclassify these lands, the national government can protect forest from agricultural conversion if it so chooses. However, both the national forestry ministry and regional land use authorities derive substantial revenues from land use concessions and transfers, which poses one of several political challenges faced by the government.⁵⁸

In parts of Latin America, the “acquisitive prescription” doctrine has allowed those who clear public forest for farming to acquire ownership after a few years. Even though this claim to public land may be restricted to farms of a certain size, large landowners can subsequently come in and assemble large

estates from the original claimants. In Colombia, for example, the principle of acquisitive prescription dates back to the original civil code. A 2002 law shortened the waiting period to acquire ownership from ten to five years after the forest has been converted to agricultural or similar productive use. One of the purposes of this legal doctrine is to prevent the possible injustice of a person abandoning land then returning to claim it after someone else has taken it over and put it to productive use. In Latin America, the principle was usually established to encourage conversion of natural lands to agricultural use. It allows seizure of government land and therefore allows people to claim ownership by clearing government-owned forest.⁵⁹ Changing such laws is fundamental to forest protection.

In Costa Rica and Brazil, changing laws on land titling so that people no longer acquire title to land by clearing it has played an important role in reducing deforestation.⁶⁰ Land titling laws can be effective in preventing conversion to cropland because such conversion involves substantial investment. If those who illegally convert fear that their claims to land ownership will not be recognized, and their future farm income jeopardized, experiences show that conversions will be reduced.

Unfortunately, although Brazil no longer promises legal title to those who deforest, it has a history of retroactively granting rights to those who illegally did so.⁶¹ This encourages new cycles of illegal land-clearing. While governments can control how and where private parties may claim ownership or rights to develop public lands, in some cases they must attempt to strike a difficult balance between enforcement of land-use restrictions and the needs of impoverished smallholders.⁶² Where farmers have clear title to their land, governments can combine enforcement with support for agricultural improvement on existing farmland to build social support.

### Implement land-use restrictions

In the case of private lands or lands on which concessions have already been granted, there is no alternative but to pass laws restricting further conversion. Costa Rica, for example, passed a law in 1996 prohibiting further forest conversion. It has been mostly effective, if not perfectly enforced.⁶³ A study of productive lands in northern Costa Rica
between 1996 and 2010 showed that the defor-
estation ban in 1996 cut in half the conversion of
mature forest to cropland—in this case mostly pine-
apple and banana plantations.⁶⁴ In 2011, Indonesia
imposed a moratorium on granting new agriculture
and logging concessions in primary forests and
peatlands.⁶⁵ Following the 2015 fires, the morato-
rium on opening peatlands was extended to cover
areas already licensed but not yet developed.⁶⁶

Establish protected natural areas

Although the mere designation of protected areas
does not guarantee protection from deforestation,
studies have generally found that such designations
typically result in lower levels of deforestation. One
global review found that areas of land designated
as a protected area (e.g., national park, wilder-
ness area, national monument) were consistently
associated with lower levels of deforestation.⁶⁷
The study concluded that the efficacy of protected
areas was probably a result of the heightened legal
protection, remoteness, and/or poor agricultural
potential.⁶⁸ The latter two features, however, high-
light a requirement of future policy. Natural areas
that might be good for agriculture are typically not
chosen to become protected areas, but in some
parts of the tropics it is these lands that are most
at risk of deforestation. Going forward, therefore,
an important strategy will be to establish a string
of protected areas to block the path of agricultural
expansion and thereby further encourage boosting
yields on existing agricultural lands.

Establish and respect Indigenous Peoples'
territories

Establishing protected lands for Indigenous
Peoples, and respecting their integrity, in addi-
tion to recognizing the legitimate claims of such
people to the land, also often leads to low levels
of deforestation.⁶⁹ The conservation of forests in
Indigenous Territories in the Xingu watershed
of Brazil is a well-documented case where tribes
guard the forests against illegal loggers, miners, and
other intruders while forests continue to be cleared
outside the territories. Community titling of indig-
enous lands appears to have significantly reduced
both forest clearing and disturbance in the Peruvian
Amazon.⁷⁰

Enforce the law

The above measures work well only if they are com-
bined with consistent enforcement.⁷¹ Law enforce-
ment can take the form of fines for illegal clearing,
seizure of illegally converted lands, evictions of ille-
gal squatters, and arrests of illegal ranchers. Three
features could help make enforcement credible and
politically supported over the long term. First, the
“stick” of law enforcement should be complemented
with the “carrot” of positive economic incentives for
those people who might be most affected. Second,
law enforcement needs to avoid being unjust or
repressive toward marginal communities, either
in reality or in perception. Third, law enforcement
needs to be fair; it should not selectively go after the
poor while letting the rich and politically powerful
go untouched.⁷²

Increase transparency of land use and land-cover
change

All the approaches to protecting natural ecosystems
listed above benefit from adequate spatial monitor-
ing which can detect adherence to and violations of
the law and land designations. “Radical transpar-
ency” made possible by modern-day monitoring
technologies (e.g., satellites, drones, cloud comput-
ing, the internet) can be a powerful foundation for
accountability and enforceability. Global Forest
Watch now has several satellite-based monitor-
ing systems on its platform, capable of detecting
the felling of trees at high spatial and temporal
resolutions and combining those data with maps of
protected areas, indigenous reserves, moratorium
boundaries, extractive industry concessions, and
more.⁷³ What is needed next are systems that can
detect clearing of any form of natural ecosystem
vegetation (beyond forests) since it is not just for-
ests that are being converted to agriculture.

Of course, any one of these measures alone will be
insufficient; it is the combination that has impact.
Brazil illustrates this potential. The country has
long had laws restricting the percentage of land on
any farm that may be cleared (the “Forest Code”),
yet enforcement lagged. Beginning around 2005,
however, Brazil moved to enforce these laws, partic-
ularly in the Amazon, resulting in large reductions
in deforestation rates, all while agricultural produc-
tion continued to increase. Brazil reorganized its
police enforcement and took actions against corrup-
tion. The country started using satellite monitoring (e.g., DETER and PRODES systems) to identify illegal deforestation in the Brazilian Amazon.⁷⁴ The country established new protected areas in the “arc of deforestation.” Perhaps most creatively, Brazil identified municipalities where deforestation was most acute and put them on a “black list” for receiving public finance and rural agricultural credit (more on this form of “linking” protection and production below).

## Linking Productivity Gains and Natural Landscape Protection

Although governments have mechanisms they can use effectively to protect natural landscapes, there are several reasons why explicitly linking such mechanisms with efforts to boost production on existing agricultural land is probably necessary both practically and politically to achieve this protection:

- **Linkage can help ensure that land protection does not undercut food production.** It will be nearly impossible to protect natural areas if yields do not grow on existing agricultural land because the unsatisfied demand for food will push up prices and increase food insecurity.⁷⁵ Not only is such a result unacceptable in and of itself, but it also would likely undermine political support for land conservation and increase the incentive for some agricultural interests to circumvent legal protections.

- **Linkage can help equitably share the burden of climate reductions.** Many relatively poor countries are currently significant sources of land-use change emissions but have small overall per capita GHG emissions. At the same time, the economies of many poor countries are heavily dependent on agriculture, and these countries face rising food needs. For them, global equity considerations require the international community to support their agricultural development on existing land in return for protecting their remaining natural landscapes.

- **Linkage can help sustain domestic political support for both goals.** Agricultural sectors that drive deforestation and other land-use change often have substantial political influence. Linking preservation of natural landscapes with strategies to increase agricultural productivity may be politically necessary at the national level to assure both national governments and agricultural sectors that agriculture can continue to prosper.

We propose three approaches to achieving such linkages:

- **Finance:** Structure domestic and international financing to simultaneously support yield gains and natural ecosystem protection and/or restoration.

- **Land-use planning:** Develop and use “living” analytical tools in the form of detailed land-use plans that prioritize areas for agricultural yield enhancement (including “climate-smart” road networks and other public infrastructure) and protect natural ecosystems.

- **Conversion-free supply chains:** Mobilize buyers, traders, and financiers of agricultural commodities to purchase or finance only commodities not linked to deforestation or other ecosystem conversions.

## Finance

Domestic and international sources of finance offer avenues for linking yield enhancements with natural ecosystem conservation.

### Domestic finance

Domestic sources of agricultural finance (e.g., national development banks, private banks) often help farmers and ranchers by providing low interest loans. To make the linkage, these loans could set eligibility conditions that preclude farmers and ranchers from converting forests or other natural ecosystems. Such lending conditions could be retrospective, wherein the bank assesses natural ecosystem clearing on the farmer's or rancher's
land in the past. If there has been clearing after a certain year, the landholder is not eligible for a loan. Alternatively, the conditions could be prospective, wherein the farmer or rancher incurs a penalty (e.g., higher interest rate, hefty fine, loan call back) if he or she clears a natural ecosystem after receipt of the loan. Such conditioned loans would incentivize the landholder to invest in improving yields on his or her existing agricultural fields instead of clearing more land.

The Brazilian Amazon provides a successful illustration.⁷⁶ Rural credit supplies about 30 percent of the annual financing of farmers and ranchers in Brazil, and thus can be a powerful lever for behavior change. In 2008, the Brazilian National Monetary Council introduced Resolution 3,545, which conditioned rural credit in the Amazon biome on proof of a farmer's or rancher's compliance with legal and environmental regulations. One of these regulations was a limit on the amount of forest that a landholder could legally clear (20 percent of

one's land). As a result, the amount of deforestation declined. According to one estimate, in the absence of the conditioned credit, deforestation rates in the Brazilian Amazon would have been 18 percent higher than actually observed in the 2009 through 2011 period.⁷⁷

This linkage has also been important to maintaining political support for Brazil's forest protection, which has played a key role in reducing deforestation rates from their peak in 2004 (though rates have recently risen again) (Figure 18-1).⁷⁸ Work by EMBRAPA, Brazil's national agricultural research institution, helped demonstrate the capacity of Brazilian agriculture to continue to grow by boosting yields without clearing more land.⁷⁹ Brazil then explicitly linked its proposals to strengthen forest protection with additional incentives for agricultural intensification, both in its 2004 action plan for forest protection and its follow-up “ABC” climate plan in 2009.⁸⁰

<figure><img src="image_130.png" /><figcaption>Figure 18-1 | Deforestation in the Brazilian Amazon has receded from historical highs</figcaption></figure>

Source: Brazilian National Space Research Institute (INPE).
## International finance

Developed countries have committed to providing billions of dollars to developing countries to help them mitigate and adapt to climate change—although only some of these funds have started to flow. But the funding for forest protection and for agricultural improvement tend to come through different channels. The World Bank, for instance, develops climate or environmental projects to protect forests and separately develops projects to boost agriculture productivity. Some countries provide funds for forest protection under the banner of REDD+ (Reduced Emissions from Deforestation and Forest Degradation in Developing Countries). At the same time, some countries provide funds for agricultural development. The link between agricultural improvement and natural ecosystem protection is rarely drawn.

This should, and can, be rectified. The main reason is to increase the likelihood of meeting both food production and forest protection needs, and preventing the needs of one from undermining the other. Linkages also would offer benefits to the key players. For example, international funders, mainly richer countries, would see their funds advancing two goals—poverty alleviation and climate protection. National governments would be able to make a more powerful case for financial support by achieving multiple objectives at once. And agricultural interests, whether big or small farmers, would improve production on their existing land while avoiding the risks of forest conversion.

Overall, there is a strong global, shared public interest in improving agricultural productivity in developing countries so long as that productivity helps protect forests. If funds are effectively linked, they can make the case for more funding, and they can provide benefits for agricultural interests that might otherwise resist forest protection.

## Land-use planning

Land-use planning is a policy tool that governments can use to concentrate agricultural production in certain, high-yielding areas while designating natural areas as protected from conversion. To achieve this goal, land-use plans will need to be specific (geospatially and more), “living,” and cover development of road and related infrastructure.

## Plans need to be specific

We believe effective land-use planning tools need to have multiple features, including the ability to achieve the following objectives:

- Characterize the location of existing production systems in as much detail as practicable to support technical and economic assessments of their potential for boosting yields.

- Apply at the local level, but aggregate production, emissions and land-use data to the regional and national level to allow assessments of national achievement.

- Identify the technical opportunities for sustainable agriculture intensification on existing agricultural lands.

- Provide analyses of the economic feasibility of improvement options for different types of farms.

- Identify the location of priority areas for sustainable intensification, and areas that must be preserved or restored.

- Identify the location of lower opportunity-cost lands when there is an unavoidable need for agricultural expansion (as discussed in Chapter 19).

Plans at this level of detail could serve many purposes:

- Guide public policies as well as public and private funders on where to invest.

- Reassure agricultural producers of their potential to increase production without clearing new lands.

- Quantify impacts on GHG emissions, including from land-use change, and how they would change with various improvements to agricultural development.

- Provide a technical basis for specific international agreements as well as domestic and international funding.

- Inform private sector and civil society priorities.
Plans need to be “living”

Such comprehensive planning tools will require detailed but evolving technical tools—not merely one-time maps and plans. Any immediate effort to develop these kinds of systems will meet resource constraints and data limitations and rely on models, such as crop models, that are imperfect. If people are to have faith in such efforts, the systems employed must be able to easily incorporate new, improved, and more detailed information as it becomes available. For such planning systems to work, they must therefore be reflected in computer-based programs that are continually updated and modified.

Supporting development of such plans should be a major concern of international institutions focused on either agriculture or climate, such as the World Bank. They should be a particular priority, as we describe in the next chapter, where agricultural expansion is inevitable, and we offer more detailed recommendations for funding such plans in that chapter.

Plans need to address roads and other infrastructure

A key use of such plans should be to identify where to build, rehabilitate, or improve roads and where to place other agriculture-related infrastructure. The only hope for reconciling the need for new roads for agricultural development in developing countries with protection of natural areas is to plan and build “climate-smart” road systems—systems that avoid incursion into remaining natural ecosystems while enhancing the ability of the agricultural sector to access markets.

Climate-smart road systems primarily involve focusing road improvements in existing agricultural areas, particularly where there is high potential for agricultural improvement. A recent study identified some priority areas at the global level for both road-building and avoiding road construction based primarily on climate-smart principles.⁸¹ It and other studies have found, for example, areas of Africa with very poor roads that could reap great benefits from merely improving existing roads (e.g., paving dirt roads), not necessarily adding major new ones.

<figure><img src="image_131.png" /></figure>
Such an approach would support high agricultural yields, keep transportation costs low, and contribute greatly to preservation of both carbon stocks and biodiversity.⁸²

In general, this planning approach should be undertaken at high resolution at national and sub-national levels and then incorporated into government land-use and infrastructure plans. It should be a prerequisite for international funding of road improvements.

## Conversion-free supply chains

Buyers, traders, and financiers of agricultural commodities can choose to purchase or finance only commodities not linked to deforestation or conversion of other natural ecosystems. Conversion-free purchasing policies have the potential to persuade farmers, agricultural companies, and even political jurisdictions (e.g., districts, states) to meet growing demand by boosting yields instead of by expanding agricultural area. Otherwise, these farmers, agricultural suppliers, and jurisdictions would risk losing business customers, market access, and finance.

The most notable deforestation-free supply chain commitment is that of the Consumer Goods Forum (CGF). The CGF now comprises 400 of the world's leading consumer goods manufacturers and retailers from 70 countries, with combined annual sales of €2.5 trillion (about $2.8 trillion). In 2010, the board of the CGF committed to achieving zero net deforestation in supply chains for four commodities by 2020 and to curtail procurement from suppliers who do not comply. These commitments cover the agricultural commodities of palm oil, beef, soy, and pulp and paper. The impact of these pledges is trickling upstream. For example, major traders of palm oil have made similar pledges to buy and sell only deforestation-free palm oil. Getting major traders involved could help ensure that the supply chain pressure reaches markets where the CGF may not have as much influence, such as palm oil for home cooking in some Asian countries. As of late 2016, more than half the companies that source palm oil and wood products had made “zero

deforestation” commitments, as well as 21 percent of companies that source soy and 12 percent that source beef.⁸³ The CGF could also reach small to medium-sized farmers or grower companies—which are not publicly visible and do not have robust sustainability commitments—if companies applied their commitment not only to their direct suppliers but also to their suppliers’ suppliers.⁸⁴

Financiers of agricultural commodities are taking steps, too. A number of banks have agreed to a Soft Commodities Compact designed to support business customers in their efforts to reduce commodity-driven forest conversion.⁸⁵ The compact commits banks to work with consumer goods companies and their supply chains to develop appropriate financing solutions that support the growth of markets producing palm oil, soy, and beef without contributing to deforestation. Twelve banks had adopted the compact as of January 2019.⁸⁶

Voluntary actions by private corporations, in part motivated by civil society campaigns, will have their greatest effect when they reach a scale sufficient to influence an entire industry and motivate national legislators. In the mid-2000s, Greenpeace launched an effort to pressure European companies not to purchase soybeans from Brazil because of deforestation. These pressures helped lead to a commitment by the Brazilian Vegetable Oils Industry Association and the National Grain Exporters Association to establish a moratorium on the production and trade of soybeans grown on lands in the Brazilian Amazon that are deforested after July 24, 2006.⁸⁷ International agricultural traders such as Cargill and Bunge played an important role. The moratorium has been quite effective in the Brazilian Amazon. In the two years before the moratorium, 30 percent of soy expansion in the Brazilian Amazon occurred on newly deforested land. Since the moratorium, the share dropped to about 1 percent; almost all of the 1.3 Mha of new soy plantings from 2006 to 2013 in the region were on previously cleared lands.⁸⁸ One study showed that the moratorium is protecting lands that could otherwise be legally converted.⁸⁹
At the same time, the moratorium did not under-
mine Brazil's soybean industry. Since implementa-
tion, soy production has continued to grow, mostly
through intensification.⁹⁰ Nonetheless, some
expansion of soybean area has occurred in the
Brazilian Cerrado and the Bolivian Amazon. This
leakage indicates that private efforts will be most
useful only when they reach a scale large enough to
motivate government policies as well.

To realize its potential, the conversion-free supply
chain model needs more companies and financial
institutions to make conversion-free supply chain
commitments so that together they account for a
significant share of market demand (or financing)
of each agricultural commodity. Otherwise there is
a risk of sizeable market “leakage,” whereby suppli-
ers merely divert deforestation-linked agricultural
commodities to a large market of buyers that have
not made commitments. Companies and banks also
need to follow through on their commitments. And
follow-through requires monitoring and account-
ability mechanisms.⁹¹ Given that commitments for
2020 will likely not be met, how the CGF and other
industry players respond and adjust their strate-
gies will be critical to the future success of this
approach.

"Jurisdictional" approaches

A potentially potent way of implementing these
three approaches is to operate at the jurisdictional
scale. The “jurisdictional approach” refers to a
comprehensive approach to land-use governance,
decision-making, and zoning across a legally
defined jurisdiction (e.g., state, district) or ter-
ritory.⁹² Part of the theory of change is that those
jurisdictions that succeed in implementing these
approaches—and thus succeed in decoupling

agriculture from ecosystem conversion—would start
to receive preferential investment by companies
and financial institutions. For example, they could
be considered “low-risk” sources of supply or safe
places for investment for companies making forest
protection commitments. Other jurisdictions might
observe these benefits and start to shift themselves.
Examples are beginning to emerge. Launched at the
Conference of the Parties (COP) 21 climate confer-
ence in Paris in 2015, the Brazilian state of Mato
Grosso’s “Produce, Conserve, and Include” strategy
and plan aims to promote sustainable agriculture,
eliminate illegal deforestation, and reduce GHG
emissions—all at the same time. Responding to con-
cerns about losing access to international soybean
markets, it has 21 performance targets and involves
40 partner organizations. Currently, deforestation
remains relatively low while the agriculture sector
in Mato Grosso, led by soybeans, thrives.⁹³

Produce, protect, and prosper

The underlying strategy of this chapter can be sum-
marized as one of “produce, protect, and prosper.”
To achieve a sustainable food future, protection
of forests and other ecosystems must occur at the
same time as enhancements in crop and livestock
yields. In addition to linking production and protec-
tion, people will need to “prosper” through the
growth of their local economies; increased security
of food, feed, and fiber; and reductions in poverty
through job and income growth. Without such ben-
efits, political support for sustainable intensification
and for conserving natural areas might be lost over
time.
<figure><img src="image_132.png" /></figure>
MENU ITEM: LIMIT
INEVITABLE CROPLAND
EXPANSION TO
LANDS WITH LOW
ENVIRONMENTAL
OPPORTUNITY COSTS

Although the goal should be to avoid all agricultural expansion, in
some locations agricultural expansion is inevitable. As discussed
in Chapter 17, agricultural land will expand for local food production
in much of Africa, for example, and oil palm plantations will
expand in Southeast Asia. In these situations, the land-use plans
we described in Chapter 18 need to guide where this expansion
should go. How should they do so?
# The Challenge

## How should we define low opportunity-cost lands?

We begin by focusing on our disagreements with some previous analyses which claim that many broad categories of land should be viewed as either “free” to use or involve little carbon cost, typically because they are not existing cropland or dense forest, or because they are forests that have recently been cut. The errors generally track those discussed in Chapter 7 regarding bioenergy, which similarly assume that these categories of land are available to grow biomass crops at no or little cost in carbon storage or food production and with low or no social opportunity costs. Examples include *abandoned agricultural land*, which is not free because it would typically regenerate to forest or other natural vegetation; *pasture land*, which both stores carbon and produces food; *woody savannas*, which store abundant carbon and tend to have high biodiversity; and *cut-over forests*, which also regenerate if left alone or replanted.

A surprising number of studies refer to the potential to expand bioenergy or crop production onto lands they term “marginal” or “degraded.”⁹⁴ Unfortunately, as well summarized by Gibbs and Salmon (2015), these terms have no precise meaning. Studies that use them offer multiple definitions but none that identify unused categories of land. These terms are frequently applied to lands that are considered marginal for cropping—but this quality does not make them marginal for purposes such as carbon storage or pasture.⁹⁵ Quite often, the terms are applied to lands already in agricultural use but typically experiencing some form of soil degradation. Their reclamation can and should be part of the effort to increase crop and pasture yields. They cannot provide lower opportunity-cost lands for agricultural expansion for the obvious reason that they are already in agricultural production. Even lands that are so unproductive that they store little carbon and produce low yields—and therefore are not good candidates for expanding agriculture anyway—are often extensively used by the poor.⁹⁶ The problem in each case is failing to recognize that virtually all land has some kind of opportunity cost.

## The opportunity

The goal is to find lands with relatively low environmental and other opportunity costs but with good productive potential on which to expand agriculture. Several principles guide the search:

- Because these opportunities are a matter of degree, a proper analysis requires far more subtle evaluation than simply assessing broadly defined land-use categories and incorporating potential food yields.

- To reflect carbon effects, the analysis must account not just for existing carbon but also for likely future carbon sequestration (e.g., from regrowing forests on abandoned agricultural land or in forest areas that have been recently harvested for wood). Each year globally, regeneration replenishes most of all annual carbon losses from forest clearing and therefore plays a fundamental role in slowing climate change.⁹⁷

- The analysis must focus not just on the loss of carbon per hectare but also on the loss of carbon per ton of crop that would likely be produced, which in turn depends on the likely yields.⁹⁸ Land may store little carbon, but if it will also produce few crops, farmers will need to clear more land and release more total carbon to produce the same amount of food.

Several studies support the hypothesis that targeting specific lands can meet food needs with lower environmental costs than using other lands. In Tanzania, one study looked at multiple criteria in addition to potential yield when considering areas for agricultural investment. Ideal areas for agricultural expansion varied depending upon whether the criteria included social capital, forest conservation, and farm management. Sometimes the use of different criteria led to conflicting answers.⁹⁹

A second study focusing on Zambia found good results from a “compromise” approach giving equal weight to maximizing potential yield, minimizing transportation costs, minimizing carbon releases, and minimizing impacts on biodiversity. Such an approach reduced the potential transportation,
carbon, and biodiversity costs by 80 percent while reducing the average potential yield of each new hectare by only 6 percent, compared to a strategy that focused on yield-enhancement alone.¹⁰⁰ This same paper showed that the “farm blocks” of land formally designated for agricultural expansion by the government were poor choices to achieve any of these four objectives.

Studies of this type recognize that land has different potentials. In general, wetter lands are more productive and better at producing crops, but they also store more carbon and support more biodiversity. Yet the relationship is not perfect. Rainfall patterns and soil types may reduce the productivity of crops more than of trees and therefore forests. Access to transportation and other infrastructure may make it more profitable to farm in one location than in another with higher, raw crop potential. Both carbon storage and biodiversity are undermined on lands with a history of human alteration. The biodiversity of any one hectare of land also depends heavily on the lands around it. If the only goal were agricultural profitability or productivity, these environmental considerations would be irrelevant. But if the goal is to achieve a sustainable food future, considering the wider advantages and disadvantages of farming different hectares of land opens up the potential to find options that are still beneficial to agricultural productivity and profitability while reducing environmental effects.

Indonesia has been a major focus of study because expansion of oil palm plantations into forests and peatlands has been occuring rapidly and because growth in global demand for vegetable oil makes some continued expansion of oil palm inevitable. One study estimated that optimal location of new oil palm plantations to double Indonesia palm oil production between 2010 and 2020 could avoid all primary and secondary forest loss. This outcome could avoid all biodiversity effects analyzed in the study, cut land-use change emissions by 30 percent, and reduce loss of other food production by two-

thirds compared to the most likely “business-as-usual” scenario.¹⁰¹ Ideally, farming would expand only into areas that have truly low environmental and social opportunity costs yet could still be productive croplands. To the extent that such lands exist, they will generally be lands that receive enough rainfall to be productive but face some kind of biological and physical barrier to significant natural regeneration.

One category of such low opportunity-cost, potentially productive land includes areas in Southeast Asia that were once logged or farmed then abandoned, and overrun by Imperata grasses. Imperata grasses store only modest quantities of carbon and will sequester little future carbon so long as they remain subject to frequent fire.¹⁰² They also support far less biodiversity than forests¹⁰³ and are of poor quality for livestock, which leaves them with limited economic benefits. And the return on investment from establishing oil palm on converted Imperata grasslands can be favorable even when compared with the return on investment of establishing oil palm on recently cleared forests.¹⁰⁴ These lands are not truly free of opportunity costs: many occur in mosaics with some tree cover and some agriculture by smallholders. This is probably why they are burned. Even the densest Imperata stands could be replanted as forests but their use for oil palm would be appropriate because the alternative would likely be clearing of valuable primary or secondary forests. Although no one really knows how much Imperata grassland there is, estimates include 3.5 Mha¹⁰⁵ in Kalimantan and 8 Mha in all of Indonesia.¹⁰⁶ In theory, this area could provide most if not all of the additional expansion needed in Indonesia for another decade.¹⁰⁷

In the real world, other factors also play an important role, including transportation access and social and legal acceptance (Box 19-1). These barriers are at least potentially subject to change with appropriate investments, zoning changes, incentives, and community outreach.
BOX 19-1 | Mapping lands suitable for sustainable oil palm expansion in Indonesia

Over the past several years, WRI has been working with Indonesian partners from government, industry, nongovernmental organizations, and research organizations to identify lands with lower environmental opportunity costs that have the potential to support sustainable oil palm plantation expansion in Indonesia.

In this mapping effort, we use an environmental suitability screen to filter out lands that, if converted to crops, would have large environmental costs in terms of carbon and/or biodiversity. In particular, it screens out all primary and secondary forests, swamps, peat soils of any depth, conservation lands and bodies of water, and their buffer zones. It also screens out human settlements, some agricultural lands,ª aquaculture ponds, airports, and other large infrastructure. Figure 19-1 (left) shows the results of applying this screen to Kalimantan, Indonesia (on the island of Borneo).

Because not all the lands that pass the initial screening will be suitable for oil palm, the method layers on additional screens. The economic viability screen identifies those areas with appropriate elevation, slope,

rainfall, soil depth, soil type, soil drainage, and soil acidity for an oil palm plantation to be profitable. Areas not meeting these criteria are eliminated from the map. Figure 19-1 (center) shows the results of layering in the economic screen.

The method then layers on a legal availability screen that factors in land-use zoning and community rights. Lands located in areas not zoned for agriculture can be difficult, but not impossible,ᵇ to convert into oil palm or other crops. Figure 19-1 (right) shows the results of layering on the legal availability screen for Indonesia.

Finally, for the areas that remain, a social acceptability screen discerns—via field-based stakeholder engagement and workshops—the interest and willingness of communities that live in and around a candidate site to have oil palm developed there. WRI's experience is that some communities support oil palm development while others do not.

As is evident from these figures, although the area of opportunity may seem large at first; the amount of land that remains practically

possible for conversion to crops (in this case oil palm) is smaller after incorporating important parameters such as economic, legal, and social factors.

The lands that meet environmental criteria are not necessarily low-cost: most of these lands would reforest if not used by people, and human uses may produce a range of small-scale agricultural products. In the face of the world's fast-growing demand for vegetable oil, however, focusing oil palm expansion on these lands constitutes a vast improvement over alternatives that directly convert valuable natural forests.

For more details about this method, see Gingold et al. (2012).

Notes:

a. The method screens out existing plantations and intensively used agricultural areas according to Ministry of Forestry land cover data. To more precisely fit the definition of lands with low environmental opportunity costs suitable for cropland expansion, the method should screen out all active cropping areas, which must be determined via field surveys.

b. It would require having the relevant zoning agency (or agencies) rezone the tract of land into a class that allows for agriculture.

<figure><img src="image_133.png" /><figcaption>**Figure 19-1** | Screening out lands that do not meet environmental, economic, and legal criteria reduces the area of land suitable for oil palm expansion in Kalimantan, Indonesia</figcaption></figure>

Source: Gingold et al. (2012).
## Recommended Strategies

Where agricultural land expansion is inevitable, selecting areas for expansion that have relatively low environmental opportunity costs is one part of the effort we describe in this course to link yield improvements and protection of natural areas. But how can governments best identify such expansion areas?

Our main additional recommendation in this menu item is for governments to develop the kinds of land-use modeling tools we describe in studies for Indonesia, Tanzania, and Zambia to identify where inevitable land expansion should take place. Such tools will have to assess yield potential, likely costs of production, and carbon and biodiversity effects. International institutions such as the World Bank should help fund them. Several aspects of this challenge merit emphasis.

**Quick results.** Because different stakeholders have different interests, a tool must quickly show the results of different compromises. Individuals and groups are more likely to find common ground if they can see outcomes and decide whether they are acceptable. The Zambia model discussed above has this kind of feature to allow stakeholders to see easily the consequences of assigning different levels of importance to different goals.

**Intuitive presentation of outcomes.** Planning tools must overcome many technical challenges. There are many data limitations, and some goals are difficult to measure because they are so complex. Biodiversity will always remain a challenge to express in one simple unit because it may be valued in many different ways. For example, analyses may focus on the total number of species using an area of land, or they may focus only on threatened species, or on different taxa (such as vertebrates or categories of vertebrates), or they may identify areas based on loss of similar habitat types. Quantitatively, each objective can be measured using different units (e.g., units of carbon, biodiversity, and profitability), which are not directly comparable. Different methods of quantification will have different results, such as ranking areas by percentile or by absolute quantities. A useful planning tool needs to present outcomes for each scenario in units that

make intuitive sense to people as far as is practicable, for example, in tons of crops per hectare, dollars of profit (if economic analysis is included in the model), and tons of carbon released. Not all modeling approaches are equally good.

**Adequate funding.** To develop and maintain a proper land-planning tool, dedicated resources are required. To focus on just one important input, estimating potential crop yield requires use of some kind of crop model. Good crop modeling requires a great deal of data, such as detailed soil data, which is typically not available broadly for all locations, and some of which may not be completely available in any location. Funds needed to be spent to make the data as accurate as possible.

**Monitoring and updating.** Resources must also be dedicated to determine whether predictions prove accurate, to reprogram the tools as necessary, and to update results as the world changes. Monitoring, recalibrating, and updating are not a one-time exercise but must be continued over time to ensure that predictions remain accurate.

Policymakers tend to be in a rush and often want results with limited resources. Because modelers can always make broad assumptions if necessary, they can generate models that look misleadingly convincing but that lack the rigor necessary to justify their use for important decisions. These kinds of mapping enterprises at the national level will require ongoing budgets in the low millions, not hundreds of thousands, of dollars. These efforts are not easy, but there is also no alternative if the goal is to achieve reasonable outcomes. International institutions that focus on climate or development need to support these efforts and use them before funding major new roads or other infrastructure investments.

For more detail, see "Limiting Cropland Expansion to Lands with Low Environmental Opportunity Costs," a working paper supporting this World Resources Report available at www.SustainableFoodFuture.org.
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# MENU ITEM: REFOREST ABANDONED, UNPRODUCTIVE, AND LIBERATED AGRICULTURAL LANDS

Some agriculture will inevitably shift from one location to another. Reforestation of abandoned agricultural land or restoration to some other natural vegetation will be required just to maintain net forest and savanna area. However, the potential for global reforestation is sometimes overestimated. Large-scale reforestation to mitigate climate change will be possible only if enough agricultural land is “liberated” through highly successful efforts to slow growth in food demand and boost agricultural productivity.
## The Challenge

Many climate mitigation strategies involve sequestering carbon by restoring land now in agricultural use to forest or other natural vegetation. “Forest landscape restoration” typically means the process of restoring ecological functionality by enhancing the number and diversity of trees on the landscape.¹⁰⁸ Restoration can start from completely deforested areas, from degraded forests, or from fragmented forests. It can end up in a variety of land covers and uses, ranging from vast tracts of dense natural forests (which would have the highest standing carbon stocks and biodiversity benefits), to mosaics of wooded areas of land adjacent to agricultural areas, to integrated agroforestry and silvopastoral systems, all the way to mosaics of commercial tree farms and natural forests.

In this chapter, we examine the subset of forest landscape restoration that returns areas of land to dense natural forests, woodlands, and/or woods adjacent to agricultural areas (i.e., reforestation). (Restoration to agroforestry or silvopastoral systems is covered in Chapters 11 and 13.) We focus this chapter still more narrowly on reforestation because forests store more carbon than any other form of terrestrial ecosystem.

Reforestation can occur in one of three ways: spontaneous natural regeneration, in which vegetation regrows without human assistance; assisted natural regeneration, in which land managers reduce obstacles to natural regeneration (e.g., remove fire or grazing animals) and then “let nature take its course”; and active reforestation, in which land managers make significant interventions to reestablish vegetation, such as growing young trees in nurseries and then planting them. Replanting can involve the use of varying mixes of natural species or only one or a few species designed to maximize wood output. But what is the real reforestation opportunity, how should land-planning efforts decide where to reforest, and how can reforestation be advanced?

Many climate studies have found a large potential for reforestation, often in the hundreds of millions of hectares. Examples include broader assessments by the Intergovernmental Panel on Climate Change (IPCC), the “Stern Report” on the costs of climate mitigation, and many original underlying studies.¹⁰⁹ One study even developed a scenario that includes

the reforestation of all grazing land that was originally forested before being converted by humans, and would therefore cover large tracts of Europe.¹¹⁰

Our analysis is less optimistic, and we explain why we disagree with these high estimates at the end of this chapter (Box 20-1). Ultimately, our analysis is not necessarily at odds with some of the more modest estimates of reforestation potential, but we believe the core condition is that “potentially reforestable” land must not also be needed for ongoing food production. Unless this condition is appreciated and taken into account, reforestation of land in one location will likely lead to more land-clearing in other locations, which undermines its environmental benefit. An alternative poor outcome is that reforestation could lead to reduced food consumption, which undermines its public benefits as well as its long-term political support.

## The Opportunity

Using this core criterion, we identify three categories of land that offer real potential for reforestation:

- **Abandoned lands.** Although abandoned agricultural lands will tend to regenerate on their own, there is potential to more actively reforest land that is abandoned as a result of agriculture shifting locations.

- **Agriculturally marginal and unimprovable lands.** These lands generate marginal agricultural output today and have little practical potential for intensification in the future.

- **“Liberated” lands.** These lands occur if demand reduction (Course 1) and productivity improvements (Course 2) result in net reductions in the area of agricultural land.

### Improved reforestation of abandoned land

Opportunities exist to enhance the reforestation of agricultural land abandoned as a result of shifting locations of agriculture, even while net deforestation occurs globally. As the satellite image studies discussed in Chapter 17 reveal, abandoned agricultural lands usually regenerate to forest anyway—sometimes naturally and sometimes with the active support of land managers and government. By around 1900, the East Coast of the United
States was largely deforested, but it now is home to extensive areas of forest; the same is true for large parts of western Europe. Although most of this land reforested naturally, the United States actively supported reforestation through the Civilian Conservation Corps during the Great Depression of the 1930s. Between the mid-1950s and 1970, South Korea invested massively in reforestation, raising the country's forest cover levels from 35 percent to 64 percent.¹¹¹ The Chinese government reports that since 1991 it has spent $47 billion to plant trees on 28 Mha of formerly marginal agricultural land.¹¹² Notwithstanding these efforts, opportunities exist to improve the quality of this reforestation both to store more carbon and to support more biodiversity and ecosystem services—in line with the goals of the broad field of restoration ecology.

As just a single illustration, researchers have shown that planting leguminous trees in abandoned fields of Brazil's Atlantic Forest region dramatically increases the rates of biomass growth and enables other, more varied trees to grow as well.¹¹³ Governments now often support reforestation of abandoned agricultural land, but they typically focus on plantation forests, often using a single fast-growing commercial tree species. These kinds of trees are better suited to meet demands for timber products and therefore also earn a more rapid economic return. However, they are less capable of storing carbon, have limited biodiversity when compared to natural ecosystems, and are more prone to risks of fire, storm damage, and pest damage.¹¹⁴ For example, a study of China's reforestation program in Sichuan province estimated that the planted forests, typically monocultures, had a dramatically lower bird and bee diversity than even the croplands they replaced.¹¹⁵

In at least some situations, planting more diverse, native, and relatively slow-growing species provides a realistic economic option, potentially producing comparable or only slightly lower economic returns. In these cases, even modest government interest in biodiversity would warrant reforestation of higher quality. Even for plantations, one study in China has shown that just mixing blocks of two to five different plantation forest types results in substantially more diverse bird populations, with no reduction in economic returns.¹¹⁶

Because agriculture is likely to continue to shift locations both within countries and around the globe—at least to some extent—the shifting will likely continue to lead to carbon and biodiversity losses unless governments adopt more policies to establish more natural forests on abandoned agricultural lands.

## Marginal lands with little intensification potential

Reforestation opportunities exist on agricultural lands that are producing only limited quantities of food today and whose potential for improved food production in future is low. Steeply sloped grazing land often falls into this category; examples include some of the pasturelands in Brazil's Atlantic Forest region. These hilly lands produce only around 30 kg of beef per hectare per year, which contrasts with the potential to produce around 150–200 kg/ha of beef on well-managed grazing land.¹¹⁷ Yet the steep slopes make impractical the critical pasture intensification options, which rely on mechanized plantings. In contexts like this, an analysis of the trade-offs between cattle intensification and reforestation would support reforestation. Little-used, drained peatlands represent another prominent example of lands with good restoration potential. Peatlands are so significant globally that we address them separately in the next chapter. We do not know how many hectares of agricultural land truly qualify as “marginal lands with little intensification potential” because no one has yet done the right kind of analysis at this scale.

Reforesting even low-yield agricultural land has some potential to lead to land-clearing elsewhere, although it is less risky than taking high-yielding lands out of production. Taking full advantage of this opportunity therefore requires some additional yield gains on existing agricultural lands or equitable demand reductions.

## Reforesting lands "liberated" by yield gains and sustainable demand strategies

Land might be liberated for potential reforestation if the strategies to moderate growth in food demand and/or increase crop and livestock yields achieve sufficient success to result in net global reductions in agricultural land area. Although we have described how challenging such goals are, some of our combined scenarios of multiple menu items
would in effect achieve net agricultural land reduc-
tions. We provide quantitative estimates of their
potential in hectares and associated reductions in
GHG emissions in the penultimate section of this
report "The Complete Menu: Creating a Sustainable
Food Future."

Overall, properly recognizing the limitations that
food production imposes on reforestation highlights
some important lessons. One is that reforestation
at scale requires reducing the need for agricultural
land first while protecting other natural areas from
conversion. Another is that, precisely because there
will probably be only limited areas where refor-
estation is the best use of agricultural land, those
opportunities need to be exploited.

Recommended Strategies

Forest landscape restoration is increasingly
prominent on the global agenda. Under the Bonn
Challenge—a global effort to bring 350 Mha into
restoration by 2030—57 national and subnational
actors have thus far committed to restore 170 Mha
(Figure 20-1).¹¹⁸ More than 100 countries have
included restoration in their nationally determined
contributions to the Paris Agreement.

Some funding has also emerged. The World Bank is investing $1 billion in restoration projects between 2015 and 2030 in Africa, and more than $2 billion in private finance has been pledged under Initiative 20x20 in Latin America.

Other reports have provided useful guidance for
moving ahead with reforestation,¹¹⁹ and we focus
here on three key recommendations for moving
forward.

<figure><img src="image_135.png" /><figcaption>**Figure 20-1** | Bonn Challenge commitments have been made by 57 national and subnational governments (as of February 2019)</figcaption></figure>

Note: Maps are for illustrative purposes and do not imply the expression of any opinion on the part of WRI concerning the legal status of any country or territory, or concerning the delimitation of frontiers or boundaries.

Source: Bonn Challenge (2019).
Properly identify "marginal and unimprovable"
agricultural lands for reforestation

In a world that needs both more food and more
carbon storage, the only way to increase both is to
make more efficient use of land. Focusing on food
and carbon storage alone, it makes little sense to
remove land from food production if that food
production is efficient or could be made efficient.
Reforestation and other forms of restoration
should in general therefore focus on land with good
restoration potential but with low food production
and limited realistic potential to improve it. For any
particular hectare, how can one know if and when
such reforestation or restoration of other natural
habitats would be a more efficient use of land?

The challenge is to find a common measure for
testing the efficiency of land use when producing
different outputs, such as different foods, bioen-
ergy, or forest. Intuitively, in a world that needs (for
example) both maize and forest carbon storage, it
is obvious that if land can produce a great deal of
maize and little forest, it is best used for maize—and
vice versa. But how much maize equals how much
forest carbon? One approach is to calculate the car-
bon opportunity cost of using land one way rather
than another.

The Carbon Benefits Index¹²⁰ provides an example
of such an approach based on the assumption
that producing a ton of any particular food in
one location will avoid the need to clear other
land to produce a ton of that same food. As a
result, the carbon savings of producing a food on
any particular hectare of land is the carbon that
would otherwise be lost on average elsewhere to
produce the same food. To estimate this “carbon
opportunity cost,” the index uses the average
global loss of carbon from vegetation and soils
that has resulted from producing a kilogram of
that particular food. Each food—for example, corn,

lentils, or chicken—has a particular cost based
on the type of land that was cleared to produce
it on average globally and the average yield of
crop. The index also incorporates differences in
production emissions, so that producing a kilogram
of a food with fewer production emissions than
the global average generates a carbon savings,
while producing a kilogram of food with higher
than global average emissions generates a carbon
cost. In addition, the index counts any increase or
loss in carbon on land as a carbon benefit or cost.
Overall, the index makes it possible to compare the
benefits in terms of total GHG emissions (CO₂e)
avoided under the alternative options of generating
a ton of any particular food, preserving land as
forest, regenerating land as forest or other natural
vegetation, or using land for bioenergy.

Using this analysis, for example, reforesting highly
sloped, poorly grazed land in the original Atlantic
Forest in Brazil produces clear net gains, but the
best use of already-cleared land for pasture in the
Cerrado would likely be to intensify its pasture
production. This index, or something similar,
could also be used to identify the most suitable
lands to convert to agriculture when agricultural
expansion is inevitable—identified in this report as
low environmental opportunity cost lands.
¹²¹

Increasing global carbon storage is not the only
goal of reforestation. Protecting biodiversity could
be reason enough to justify reforestation of some
areas, even of productive agricultural lands, as
could preventing high levels of erosion or encourag-
ing tourism. Yet for climate purposes, the general
principle should be that governments encourage
changes in land use from one category to another
when doing so would result in a sizeable net per-
centage increase in global carbon benefits. Mitig-
gating climate change while meeting food needs
will require that land-use decisions maximize the
output of each hectare of land.