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A Geospatial Analysis of Future Food Demand and Carbon- Preserving Cropland Expansion: Implications for Tropical Regions

  1. Justin Johnson, Ben Senauer & Ford Runge Paper co-authors: Jonathan Foley and Stephen Polasky
  2. Feed 9 Billion People by 2050 The Challenge:
  3. How can we feed this many people while minimizing environmental degradation?
  4. Increasing yields on existing croplands will meet 70-80% of future food demand. But yield increases are slowing. Assume need for 25% expansion in cropland
  5. Some Cropland Expansion is Necessary • Yield increases alone are insufficient to produce 100% more calories by 2050 • The problem: • Cropland expansion dramatically reduces environmental value Source: Ray et al. 2013
  6. For the all arable hectares on Earth, we ask: should we cultivate this field to grow food… or protect it to preserve environmental value?
  7. Natural lands provide Ecosystem Services • “Natural processes that provide economic value to humans” • Water purification • Soil quality • Pollination of crops • Climate regulation • From carbon storage
  8. Identifying the optimized trade-off globally • We use high-resolution remote sensing data combined with regular ground- based surveys. • Data divides the earth into 5x5 minute grid-cells. • Approximately 10x10 km at the equator. About 10 million globally. • To say more precisely where we should expand agriculture
  9. Graphical description of our method • For each grid-cell, define the comparative advantage of food production relative to the loss of carbon storage • In this example, a higher number means the grid-cell is relatively good at producing food • The color corresponds to the number .25 .5 1 .12 3 1 .12 .5 2
  10. Calories per tons of carbon storage 0 300,000 500,000 We Apply this Approach Globally
  11. Methodology of Crop Advantage • We define the relative advantage of cultivation for every grid-cell as “Crop Advantage” • Crop Advantage = Calorie Yield / Carbon Loss 𝐶𝐴 = 𝐶𝑌 Δ𝐶 • This represents net benefit of converting land to cultivation while taking into account marginal costs of carbon loss
  12. Calories per Grid Cell 0 1e+11 2e+11 This defines the numerator in crop advantage: caloric yield.
  13. This defines the denominator of crop advantage: carbon storage change. Carbon Storage Loss
  14. Calories per tons of carbon storage 0 300,000 500,000 The ratio of these defines Crop Advantage How do we use crop advantage to define the optimal areas to extensify?
  15. Optimization Method
  16. The Food-Carbon Tradeoff • We need to increase food production by 100% by 2050 • What about carbon? 100% more food Current food production Food Produced (quadrillion calories) 0 11 22
  17. The Food-Carbon Tradeoff • Add carbon storage on the vertical axis • Every point represents a combination of carbon storage and food production • For example, suppose we currently are at the indicated point • When we produce more calories, we will likely lose carbon CarbonStored Food Produced (quadrillion calories) 0 11 22 Situation today Produces enough calories but loses carbon storage
  18. The Food-Carbon Tradeoff • Our optimization approach checks all possible choices of where cropland can expand • Identifies which choices result in the least amount of carbon loss. • Restrict our analysis to grid- cells between 5 & 95% cultivated. CarbonStored Food Produced (quadrillion calories) 0 11 22 Potential future scenarios Situation today Optimal future scenario
  19. Define Two Scenarios • 1.) Carbon-Selective Scenario (optimal) • Expand cultivation on the land that minimizes carbon loss while meeting caloric targets • 2.) Business as Usual (BAU) Scenario • Expand cultivation to meet caloric targets, but ignore carbon storage • We compare these scenarios to see what we need to do differently
  20. Present Situation Carbon-Selective Scenario BAU Scenario BAU land-use (based on existing policy, market forces and other drivers) Carbon-Selective land-use (based on same drivers) Comparing these two scenarios shows what we need to do
  21. Comparison of Optimal vs. BAU Scenarios Proportion of grid-cell preserved -0.5 0 0.5 Green cells indicate where the optimal scenario preserves more land than BAU. Red means the optimal solution loses carbon storage relative to BAU.
  22. Zoomed in on the U.S. Corn Belt and S.E Asia
  23. Crop Advantage (calories per tons carbon storage) 0 300,000 500,000 Proportion of grid-cell preserved from extensification -0.5 0 0.5 Expand at the edges of existing agricultural centers • Places like the Corn Belt & SE Asian deltas have extremely high crop advantage (top) • But these areas already are near or at maximum cultivation • The best remaining areas are on the edges of the high CA areas
  24. Tons per grid-cell -15,000 0 15,000 Net Carbon Storage Change. All together, this is 6 billion metric tons of carbon saved How much carbon did we save?
  25. Value using a Social Cost of Carbon Climate scientists calculate that a ton of carbon storage is worth $181 in avoided climate change damages. Thus, we save $1.06 trillion by optimizing by 2050.
  26. Policy Discussion • Smartly expanding agriculture saves a very large amount of carbon. • If we want to minimize carbon loss, we should target cropland expansion on the edges of existing bread baskets, not in carbon-rich areas. • Even when considering food security, forests are almost always worth protecting rather than cultivating, especially tropical rainforests. • The $1.06 trillion figure likely underestimates the value dramatically • Only one ecosystem service considered
  27. Policy Discussion • Optimal expansion is difficult. • We may not get there, • but knowing the full costs helps us know how to move toward the optimum. • Future research will add more detail: • More information on costs of intensification and expansion • More ecosystem services • More specific policies: Food-for-Nature Payments • Currently analyzing various combinations of intensification & extensification. • 70% increase in caloric needs; consistent with the economics literature. • And potential policy incentives.
  28. For Further Information • Justin Andrew Johnson, Carlisle Ford Runge, Benjamin Senauer, Jonathan Foley, and Stephen Polasky. 2014. “Global agriculture and carbon trade-offs”. Proceedings of the National Academy of Sciences, vol. 111, no. 34 (August 26): 12342-12347. (Supplemental Information, 14 pages)

Editor's Notes

  1. Range of caloric demand by 2050 vary from 50% to more than 110% We focus our analysis on meeting a 100% increase, in line with the estimates in Tilman et al. (2011)
  2. What do we mean by environmental value? A useful way of approaching this question is in the framework of ecosystem services. We focus on climate regulation and how it is affected by carbon storage
  3. Ratio of aggregate calories produced divided by carbon storage on each 5x5 minute grid-cell. Red values indicate areas where crop cultivation is comparatively advantaged over carbon storage.
  4. where 𝐶𝑌 represents caloric yield per grid-cell aggregated over 175 crops using the current mix of crops grown (Monfreda et al. 2008), and Δ𝐶 is the tons of carbon storage lost (including aboveground, belowground and soil carbon) per grid-cell when a cell is converted from grassland or forest into cropland. To calculate carbon storage loss per unit area, we compare carbon storage in potential natural vegetation to carbon storage in crops. Carbon storage in potential natural vegetation and the methods for calculating crop carbon are from West et al. (2010) (see Methods and Supporting Information for details).
  5. Ratio of aggregate calories produced divided by carbon storage on each 5x5 minute grid-cell. Red values indicate areas where crop cultivation is comparatively advantaged over carbon storage.
  6. Both the optimal and the BAU simulation produce 100% more calories and assume 25% of the calories come from extensification. Blue and green shading indicate areas where less extensification would occur under the optimal solution compared to BAU. Red and yellow shading indicates areas where more extensification would occur under the optimal solution compared to BAU.
  7. Sawmill in forest analogy Central place theory comment
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