suffer negative health consequences due to heat. The second aspect of the impact of heat is more obvious: increases in crop labor requirements result in higher production costs, which could translate into higher food prices, reduced margins, or both. We note that the agricultural labor force is made up of mostly Mexican and Central American workers, often at a disadvantage in terms of legal status and subject to abuse and neglect in terms of complying with regulations that mitigate heat impacts on worker’s health. Medical research has taken important steps in documenting health impacts of heat occurrence. Our chapter makes important contributions to the analysis of the economic impact of heat on agricultural labor. That said, more research is need on this field.
An important caveat of the modeling approach used in the analysis is that the results are highly aggregated at the regional (county) level out of necessity, because the data did not support a crop‐by‐county approach. On a more positive note, the results enable analyzing the impact of heat on each crop and, thus, enables planners and others to look at specific market conditions for particular segments of the agricultural sector. In addition, because the results are crop specific and incorporating mitigating measures to reduce the impact of heat on labor can be implemented in specific ways that would not have been possible if we had been able to complete the analysis by county without specifying the crop.
ACKNOWLEDGMENTS
The authors gratefully acknowledge financial support from the National Science Foundation grant No. 1243333 “Collaborative Research: EaSM2 advancing extreme value analysis of high impact climate change and weather events.” Castillo gratefully recognizes support from the Planetary Health Centers of Expertise, and the College of Natural Resources, University of California, Berkeley. Wehner was supported by the US Department of Energy, Office of Science, Office of Biological and Environmental Research, Climate and Environmental Sciences Division, Regional & Global Climate Modeling Program, under Award Number DE‐AC02‐05CH11231.
APPENDIX 2.1
Crops Included in the Study and Harvesting Months for Each Crop and County.
| County: Fresno | |
| Crop 1: Alfalfa | Harvest months: May–November |
| Crop 2: Almonds | Harvest months: August–September |
| Crop 3: Grapes | Harvest months: June–November |
| Crops 4: Melons | Harvest months: July–September |
| Crops 5: Onions | Harvest months May–September |
| County: Kern | |
| Crop 1: Alfalfa | Harvest months March–October |
| Crop 2: Almonds | Harvest months: August–October |
| Crop 3: Grapes | Harvest months: June–November |
| Crops 4: Melons | Harvest months: June–July |
| Crops 5: Onions | Harvest months: May–August |
| County: San Joaquin | |
| Crop 1: Alfalfa | Harvest months: April–September |
| Crop 2: Almonds | Harvest months: August–October |
| Crop 3: Grapes | Harvest months: July–December |
| Crop 4: Melons | Harvest months: May–September |
| Crop 5: Onions | Harvest months: April–June |
| County: Yolo | |
| Crop 1: Almonds | Harvest months: August–October |
| Crop 2: Alfalfa | Harvest months: January–December |
| Crop 3: Grapes | Harvest months: September |
| Crop 4: Melon | Harvest months: June–July |
| County: Imperial | |
| Crop 1: Alfalfa | Harvest months: February–October |
| Crop 2: Melons | Harvest months: May–July |
| Crop 3: Onions | Harvest months: April–May |
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