Agriculture has an enormous footprint—by some estimates, it accounts for more than 90 percent of humanity's water use. One of the other areas where its footprint is felt is in carbon emissions. Converting land to agriculture disrupts the existing soil ecosystem, releasing carbon stored there into the atmosphere; a large fraction of humanity's collective carbon emissions fall under the category of "land use change."

In the developed world, the intensification of agriculture has actually allowed some formerly farmed areas to revert to something akin to their original state. But it's unclear whether there are limits to that intensification that will eventually force us to bring more agricultural land into use. Even if we don't run into limits, population growth means that it will have to scale quickly, as global food demand is expected to increase by at least 70 percent by the middle of the century.

A new paper in this week's PNAS examines whether there are ways to add significant new agricultural land without causing a huge boost in carbon emissions. It finds that it's possible to greatly expand farmed land while avoiding billions of metric tons of carbon emissions, but doing so would require a level of international cooperation that would be unprecedented.

To understand the tradeoff between agricultural land and carbon storage, the authors devised a very simple measure that they called "crop advantage," or CA. CA is calculated by figuring out the calories that could be gained by converting land to agriculture and dividing that by an estimate of how much stored carbon would be liberated by the change in land use. The caloric yield is based on the existing mix of 175 crops grown for agricultural purposes.

They then applied this measure to the Earth as a whole, laying a grid down over its surface that, at the equator, produced areas roughly 10 kilometers square. They excluded any areas that had less than five percent agriculture in them, since this likely meant they were either desert or glacier covered and incapable of supporting crops, or simply had no infrastructure to support significant farming (like the Congo basin). The latter category of grid cells would probably have a lousy CA value anyway, since they store so much carbon. The authors also excluded regions that were over 95 percent farmed, as these offer little space for additional crops.

The highest value grid squares in this analysis produced 300,000 calories for every ton of stored carbon liberated. Many of these areas were on the edges of existing farmed areas in the US, Europe, and eastern China; others were along major river valleys, like the Nile and Ganges.

They next modeled what would happen if we expanded cropland in the future. In one scenario, they simply did business as usual, adding land on the edges of existing agricultural areas. In another, they optimized the land added using their CA values, with the highest value land used first. In the first instance, they expanded agricultural land by 25 percent, figuring that the rest of the world's needs could be met through intensification of existing agricultural land in areas like Africa.

In this scenario, optimizing by CA netted a savings of six billion metric tons of carbon emissions. Based on various estimates of the social cost of carbon, that would have a value of roughly one trillion US dollars. And, at least within the range we're likely to need to expand, the scaling is linear; a 50 percent expansion of agricultural land using an optimized approach would save 12 billion tons of carbon emissions. Most of the newly farmed land would be at the edge of the US Corn Belt and in the river basins of Southeast Asia, "such as the Mekong Delta and Red River in Vietnam, the Irriwaddy River Basin in Myanmar, and the Chao Phraya River Basin in Thailand."

The one thing you may notice is that those regions are in different countries. Also notable is that many countries, including some with a substantial agricultural economy, would largely be left out of this expansion. All of which raises the question of whether this is an empty intellectual enterprise, something the authors seem to acknowledge by writing, "Showing what is possible and actually achieving it are not the same thing."

But the tool could be used for regional planning within some countries. And the authors point out that it's flexible; by tweaking the inputs, it can be adapted to a variety of other purposes—figuring out how much expanded urbanization would cost in terms of the loss of water filtration by wetlands, for example. All you need to do is put a dollar value on ecosystem services.

PNAS, 2014. DOI: 10.1073/pnas.1412835111 (About DOIs).