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Kari E. Skaggs and Suat Irmak

1. Introduction The impacts of climate change on agriculture are dependent on the magnitude and type of climate change and the mitigation and adaptation practices undertaken by agricultural producers and managers ( Parry 1989 ; Easterling et al. 1993 ; Southworth et al. 2000 ). By considering the observed trends, adjustments and adaptations will need to be made in order to exploit favorable agricultural conditions and to mitigate negative effects in maintaining optimal agricultural

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George B. Frisvold and Anand Murugesan

used in regression analyses (regressions are used to test hypotheses concerning determinants of weather data use); (iv) discuss results; and (v) summarize main findings and suggests areas of future research. 2. Empirical specification Here, we introduce a discrete choice framework that treats acquisition and use of weather data as part of an agricultural decision-maker’s utility function. Utility is a measure of benefit or satisfaction the producer derives. Information use is a choice variable

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Linda Stalker Prokopy, Tonya Haigh, Amber Saylor Mase, Jim Angel, Chad Hart, Cody Knutson, Maria Carmen Lemos, Yun-Jia Lo, Jean McGuire, Lois Wright Morton, Jennifer Perron, Dennis Todey, and Melissa Widhalm

1. Introduction Growing sufficient food, fuel, and fiber to meet the world’s needs in a sustainable manner is dependent upon favorable weather conditions. The upper midwestern United States, commonly referred to as the Corn Belt, produces more than one-third of the global supply of corn ( USDA NASS 2011 ; USDA FAS 2012 ). Short and long-term weather patterns affect agriculture in this region and are expected to become increasingly variable due to climate change ( Karl et al. 2009 ). Modern

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Rachel E. Schattman, Stephanie E. Hurley, Holly L. Greenleaf, Meredith T. Niles, and Martha Caswell

1. Introduction Climate change and shifts in weather patterns are expected to present many challenges to agricultural sectors worldwide ( Hatfield et al. 2018 ; Walthall et al. 2012 ), as changing temperatures, precipitation regimes, pest and disease pressure, and rising instances of extreme weather events put increasing pressure on existing productions systems ( Gowda et al. 2018 ). Agricultural systems are vulnerable to changing climatic conditions, with potential impacts spanning economic

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Tonya Haigh, Lois Wright Morton, Maria Carmen Lemos, Cody Knutson, Linda Stalker Prokopy, Yun Jia Lo, and Jim Angel

1. Introduction U.S. agriculture produces almost $330 billion annually in agricultural commodities and is vulnerable directly and indirectly to changing climate conditions and extreme weather events that impact crop and livestock productivity and pest and pathogen pressures ( Harwood et al. 1999 ; Walthall et al. 2012 ; Pryor 2013 ; Melillo et al. 2014 ). The recently released U.S. National Climate Assessment points out that the success of farmers in managing climate risks depends upon their

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Julie A. Silva and Corene J. Matyas

1. Introduction The endemic poverty of rural agriculturalists in many less developed countries (LDCs), together with growing evidence of climate change, has led to increasing interest in the effects of weather on the well-being of these populations. Since the 1960s, the dominant approach to rural development in low-income countries has focused on strengthening the small-farm agricultural sector in order to alleviate rural poverty ( IFPRI 2002 ; Ellis and Biggs 2001 ; Ellis 2000 ). Yet, the

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Michael J. Glotter, Elisabeth J. Moyer, Alex C. Ruane, and Joshua W. Elliott

1. Introduction Understanding future food production is critical in conditions of changing climate and growing population ( Porter et al. 2014 ). Meeting agricultural food demand that is estimated to increase by ~60% by 2050 ( OECD/FAO 2012 ) presents a significant challenge for future society. Changing demand coupled with changing production will likely have significant impacts on food availability, and subsequently affect food prices ( Nelson et al. 2014 ) and migration patterns ( Feng et al

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Ellen Jasinski, Douglas Morton, Ruth DeFries, Yosio Shimabukuro, Liana Anderson, and Matthew Hansen

in Mato Grosso has increased at an average rate of 19.4% yr −1 since 1999. Plans to further expand Mato Grosso’s soy growing area can easily be realized if market demand and public policy continue to support growth. Few natural barriers are foreseen for expansion in this region. Brazilian and foreign agricultural experts agree that approximately 100 × 10 8 ha of cerrado land is technically viable for expansion of soy in Brazil ( Schnepf et al. 2001 ; Dros 2003 ). The only obstacle at present

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Francisco J. Meza, James W. Hansen, and Daniel Osgood

1. Introduction The year-to-year variability of the climate is a serious challenge for agriculture. Beyond its direct impacts on production and market prices, the uncertainty associated with climate variability is a challenge to management, as farmers must make many critical, climate-sensitive decisions months before the impacts of climate are realized. Climate variability imposes costs on farmers predominantly through two different mechanisms, the first primarily driven by information

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Rahul S. Todmal

Tallaksen 2000 ). During the drought period, water scarcity affects all human activities in general and agricultural activities in particular, leading to reductions in agricultural production and productivity in the arid and semiarid regions ( Das et al. 2003 ; Pandey et al. 2008 ). To quantify various characteristics of drought, operational definitions are constructed in the form of drought indices ( Smakhtin and Hughes 2004 ). As drought is a relative phenomenon ( Van Loon 2015 ), various region

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