Global food demand and the sustainable intensification of agriculture

Abstract

Global food demand is increasing rapidly, as are the environmental impacts of agricultural expansion. Here, we project global demand for crop production in 2050 and evaluate the environmental impacts of alternative ways that this demand might be met. We find that per capita demand for crops, when measured as caloric or protein content of all crops combined, has been a similarly increasing function of per capita real income since 1960. This relationship forecasts a 100-110% increase in global crop demand from 2005 to 2050. Quantitative assessments show that the environmental impacts of meeting this demand depend on how global agriculture expands. If current trends of greater agricultural intensification in richer nations and greater land clearing (extensification) in poorer nations were to continue, ~1 billion ha of land would be cleared globally by 2050, with CO(2)-C equivalent greenhouse gas emissions reaching ~3 Gt y(-1) and N use ~250 Mt y(-1) by then. In contrast, if 2050 crop demand was met by moderate intensification focused on existing croplands of underyielding nations, adaptation and transfer of high-yielding technologies to these croplands, and global technological improvements, our analyses forecast land clearing of only ~0.2 billion ha, greenhouse gas emissions of ~1 Gt y(-1), and global N use of ~225 Mt y(-1). Efficient management practices could substantially lower nitrogen use. Attainment of high yields on existing croplands of underyielding nations is of great importance if global crop demand is to be met with minimal environmental impacts.

Fig. 1.

Annual dependence of per capita demand for (A) crop calories and (B) protein on per capita real GDP for each of economic Groups A–G (SI Materials and Methods). Each color of points shows the trajectory for a particular economic group (one point per year for each group). Curves are fitted to the square root of per capita GDP.

Fig. 2.

(A) Per capita GDP, (B) per capita demand for crop calories, and (C) per capita demand for crop protein in 2005 (black) and mean projected 2050 increases (white; percent increases above bars).

Fig. 3.

Projections of 2050 values for (A) global yields, (B) global land clearing, and (C) global agricultural GHG emissions and (D–F) the yields and environmental impacts of four alternative hypothetical trajectories along which agriculture might develop by 2050. Tonnes CO₂e in (C) and (F) represents the equivalent tonnes of C that would have been emitted had all GHG emissions in our analyses been in the form of CO₂. All abscissas are global annual N use in 2050 calculated as the sum across all economic groups of N use intensity (N ha⁻¹) times total cropland area (ha) needed to meet projected 2050 caloric demand. To derive the curves shown, current N use intensities of lower-yielding nations were strategically increased to equal global mean intensity, which was set at 60, 80, 100, 120, 140, or 160 kg ha⁻¹ to calculate the 12 points shown for each curve (SI Materials and Methods). The four curves shown in each graph (magenta, current technology; blue, improvement only; orange, technology adaptation and transfer only; green, improvement and technology transfer) are regression-based estimates of yields (A and D) and associated land clearing (B and E) needed to meet 2050 global caloric demand and resultant GHG emissions (C and F). Land clearing = (cropland needed to meet 2050 crop demand) − (2005 cropland).