a 10 percent higher urban expansion rate in 2100 are likely to have only a 1.6 times higher livestock density in 2010. As mentioned above, the magnitudes for the correlation between future urban expansion and current livestock production are much higher than those for the correlation between future expansion and current crop production.

_Table 5. Grid level regressions of livestock production on urban expansion rates for five SSP scenarios_

|_Outcome:_|(1)|(2)|(3)|(4)|(5)|
|---|---|---|---|---|---|
|Livestockproduction(2010, mt)|SSP 1|SSP 2|SSP 3|SSP 4|SSP 5|
|_Panel A: Urban expansion to 2040_||||||
|Urban expansion rate in 2040|604,006***|628,556***|887,535***|621,852***|481,385***|
||(2952.30)|(3116.5)|(4006.3)|(3121.1)|(2544.2)|
|Observations|2,014,887|2,014,887|2,014,887|2,014,887|2,014,887|
|R squared|0.0204|0.0198|0.0238|0.0193|0.0175|
|Mean livestock(popdensity)|13021.28|13021.28|13021.28|13021.28|13021.28|
||(6)|(7)|(8)|(9)|(10)|
||SSP 1|SSP 2|SSP 3|SSP 4|SSP 5|
|_Panel B: Urban expansion to 2100_||||||
|Urban expansion rate in 2100|291,822***|302,128***|442,168***|293,287***|163,586***|
||(1732.26)|(1684.69)|(1916.40)|(1678.8)|(1095.79)|
|Observations|2,014,887|2,014,887|2,014,887|2,014,887|2,014,887|
|R squared|0.0139|0.0157|0.0257|0.0149|0.0109|
|Mean livestock(popdensity)|13021.28|13021.28|13021.28|13021.28|13021.28|

Robust SE in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Grid-level OLS estimation, where one grid has a spatial resolution of 1/12 degree - about 9 to 10 sq km. Urban expansion rate is the percentage expansion in urban area in a given SSP scenario (ranging from 0 to 1). Livestock production is the global population densities of eight types of livestock: cattle, buffaloes, horses, sheep, goats, pigs, chickens and ducks in each land pixel at a spatial resolution of 0.083333 decimal degrees (approximately 10 km at the equator). Here, the urbanization rate is defined as the percentage of urban population to total population, and ranges from the value of 0 to 1. The urban expansion projection data (Chen et al. 2020) are calculated using panel data regression based on historical population, urbanization rate, and gross domestic product (GDP) data.

# **4. Conclusions**

This paper finds that, if poorly managed, urban expansion will be tied to a projected decline in key crops and animal-source foods that are important for diets and nutrition. There are important regional differences as well as differences across SSP scenarios and through time.

Under SSP1, by 2100, the largest projected decline among crops is for fruits, vegetables, and tubers/roots, and the smallest declines are for oils, sugar, and pulses (relative to current levels of production). Although food production initially declines faster under SSP1 than under SSP3 to 2040, it then slows so that the projected decrease in food production by 2100 somewhat aligns for both the SSP1 and SSP3 scenarios. Under SSP1, by 2100, there is also a projected decline in the number of livestock, important to the production of animal-source foods rich in protein. The largest declines are for poultry (chickens and ducks) and pigs, and the smaller declines are for ruminants (cattle, sheep, and goats). This aligns with the notion that the production of poultry and pigs is more peri-urban than that of ruminant production. By 2100, the largest urban overlap with food 24