Extreme Events and Climate Change. Группа авторов

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In J. J. McCarthy, O. F. Canziani, N. A. Leary, D. J. Dokken, & K. S. White (Eds.), Climate change 2001. Impacts, adaptation, and vulnerability (pp. 913–967). Cambridge University Press.

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      23 United Nations. (1992). United Nations Framework Convention on Climate Change. FCCC/INFORMAL/84, https://unfccc.int/resource/docs/convkp/conveng.pdf

      24 United Nations. (2015). Adoption of the Paris Agreement. FCC‐C/CP/2015/L.9/Rev.1. https://undocs.org/en/FCCC/CP/2015/L.9/Rev.1

       Federico Castillo1, Armando Sánchez Vargas2, J. K. Gilless1, and Michael Wehner3

       1Federico Castillo and J. K. Gilless work at the University of California, Berkeley, Department of Environmental Science, Policy, and Management, Berkeley, California

       2Armando Sánchez Vargas works at the Institute of Economic Research of the National Autonomous University of Mexico (UNAM), Mexico City, Mexico.

       3Michael Wehner works at the Lawrence Berkeley National Laboratory, Berkeley, California.

      ABSTRACT

      This chapter analyzes the impact of heat waves on the productivity of selected crops in California’s agricultural sector. We use a panel data ensemble to estimate the impact of heat waves on agricultural labor and the subsequent impact on crop productivity. Data used include crop prices, acreage harvested, crop labor requirements, production costs, capital, and the heat index. The counties included in the study are Fresno, Yolo, Kern, San Joaquin, and Imperial. Our results indicate that the impact of heat waves on a relatively labor‐intensive crop such as watermelons can be significant because an increase in the number of days that exceed the range of 95OF to 100OF to over 100OF results in productivity decreases on the range of 4% to 6%. For onions our results indicate that the decline in productivity is less but significant in terms of dollar amounts. Our research is an improvement on previous studies that have analyzed the impact of temperature on agricultural production in that our framework isolates the impact of heat on labor first and then incorporates it into a production function instead of using temperature as a regression variable directly, which could result in spurious outcomes. Our method complements other studies that have analyzed the impact of extreme temperatures on crop productivity and using an agronomic modeling approach.

      The agricultural sector of California is an important component of the overall US agricultural sector.

      2.1.1. Production

      Source: California Department of Food and Agriculture (2018).

Commodity (2017 ranking) Value (US $1,000) (in decreasing order) 2015 Ranking
Milk and cream 6,651,720 1
Grapes 5,793,217 3
Almonds (shelled) 5,603,590 2
Berries, all strawberries 3,100,215 6
Cattle and calves 2,625,413 4
Lettuce, all 2,414,669 5
Walnuts 1,593,900 9
Tomatoes, all 1,054,001 7
Pistachios 1,014,507 13
Broilers 939,409 12

      Source: California Department of Food and Agriculture (2018).

County Total Value (US $1,000) Leading Crops
Kern 7,254,004 Grapes, almonds, pistachios, milk
Fresno 6,369,926 Milk, grapes, cattle and calves, oranges
Monterrey

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