A Geospatial Analysis of Future Food Demand and Carbon- Preserving Cropland Expansion: Implications...
Transcript of A Geospatial Analysis of Future Food Demand and Carbon- Preserving Cropland Expansion: Implications...
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Justin Johnson, Ben Senauer & Ford Runge
Paper co-authors: Jonathan Foley and Stephen Polasky
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Feed 9 Billion People by 2050
The Challenge:
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How can we feed this many people while
minimizing environmental degradation?
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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
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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
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For the all arable hectares on Earth, we ask:
should we cultivate this field to grow food…
or protect it to preserve environmental value?
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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
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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
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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
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Calories per tons of carbon storage
0 300,000 500,000
We Apply this Approach Globally
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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
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Calories per Grid Cell
0 1e+11 2e+11
This defines the numerator in crop advantage: caloric yield.
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This defines the denominator of crop advantage:carbon storage change.
Carbon Storage Loss
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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?
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Optimization Method
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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
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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
Car
bo
n S
tore
d
Food Produced (quadrillion calories)0 11 22
Situationtoday
Produces enough calories but loses carbon storage
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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.
Car
bo
n S
tore
d
Food Produced (quadrillion calories)0 11 22
Potential future scenarios
Situationtoday
Optimal future scenario
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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
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Present Situation
Carbon-Selective ScenarioBAU 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
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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.
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Zoomed in on the U.S. Corn Belt and S.E Asia
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Crop advantage and extensification in optimal and BAU simulations for the U.S. Corn Belt (left) and S.E. Asia (right).
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
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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?
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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.
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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
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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.
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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)
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