|Livestock, 2010, mt|2,014,887|13021.28|<br>73234.23|0|1060007|
|---|---|---|---|---|---|
|_Buffaloes,_|2,008,899|94.980|906.527|0|119607.5|
|_Goats_|2,014,567|475.125|2351.833|0|237936.2|
|_Cattle_|2,014,533|723.358|1943.561|0|328070.9|
|_Sheep_|2,014,215|558.121|1885.496|0|344862.1|
|_Horses_|2,013,909|30.783|153.932|0|105564.2|
|_Pigs_|2,014,572|484.444|2889.772|0|411115.7|
|_Chickens_|2,014,564|9994.698|67859.33|0|10500007|
|_Ducks_|2,012,134|663.042|7095.628|0|1311365|

Note: Data for livestock cover not available. One grid cell has a spatial resolution of 1/12 degree - about 9 to 10 sq km. Urban extent is the percentage of urban area in a grid cell (ranging from 0 to 1). Crop production for each grid cell is defined as the yield multiplied by harvested area in metric tons. Food crops include cereals, fruits, oils, pulses, roots, sugar, vegetables food groups. 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 1/12 degree degrees (approximately 10 sq km at the equator). Missing values in the crop production dataset are specifically distinguished from crops that are not grown in a particular area. Crops not grown in an area are coded as zero, while crop data that is not available is coded as a missing value. This distinction is important as it helps to differentiate between areas where crops are not grown and areas where data is simply not available (Yu et al., 2020).

_Table 3. Baseline values for crop production and livestock production_

||**Global**|**Africa**|**EAP**|**ECA**|**LCR**|**MENA**|**SOA**|**Other**|
|---|---|---|---|---|---|---|---|---|
|**Food crops 2010**|||||||||
|**, ,**<br>**metric tons (mt)**|7,510.9|575.0|2,263.5|636.7|1,435.5|226.6|1,049.9|1,323.7|
|_Fruits and Vegetables_|1,611.6|102.2|742.8|120.3|150.3|102.3|195.7|197.8|
|_Cereals and roots_|3,207.0|350.9|948.9|385.7|232.3|82|430.9|776.4|
|_Sugars and oils_|2,625.0|108.5|561.6|125.7|1,046.3|40.5|405.6|336.8|
|_Pulses_|67.3|13.4|10.1|5|6.6|1.8|17.6|12.7|
|**Livestock, 2010, mt**|24,884.6|1,997.1|9,503.5|1,638.0|3,599.1|2,020.2|1,983.5|4,143.5|
|_Poultry_|20,451.1|1,137.5|8,363.1|1,355.6|3,008.5|1,777.2|1,322.1|3,487.1|
|_Pigs_|939.3|31.0|538.9|64|82.4|0.1|12.6|210.4|
|_Ruminants_|3,494.1|828.6|601.6|218.4|508.2|243|648.8|445.6|

Note: Since urban expansion data use 2015 as the starting year, any crop or livestock that overlap with the 2015 urban extent are not counted toward the initial agricultural production.

In Table 3, we present descriptive statistics on the percentage of grids that have overlap in urban extent, crop production, and livestock production. For example, 30 percent of grids that have cereal production also have fruit production, 90 percent of grids have both pig and chicken production, 35 percent of grids have both cereal production and pig production, 4 percent of grids have urban area and cereal production, and 5 percent of grids have urban area and pig production.

# **3. Results**

We present spatial projections of the overlap of climate-induced urban expansion with crop and livestock production under each of the five SSP scenarios (or what we call, projected losses). In Section 3.1 we present projected losses in global crop production, in Section 3.2 we present projected losses in global livestock production. In Sections 3.3 and 3.4 we present regional disaggregation of projected losses for crop and livestock production, respectively. In Section 3.5, we depict urban expansion and crop and livestock production for six selected cities. Finally, in 11