2. Projections of climate change

and increases in future production is understanding how climate change will impact this trend in corn production and the areas of the world where corn is produced. Corn is a grain crop with both food and feed uses and variation in production at the local scale can have major

Figure 2. Deviations from the yield trend line for corn production in the United States from 1950 to 2017. (data obtained

Figure 1. World corn yield and area harvested since 1960 (data obtained from FAO stat, http://www.fao.org/faostat/en,

downloaded March 8, 2018).

96 Corn - Production and Human Health in Changing Climate

The trend line for corn yield has shown a steady increase and a small amount of variation among the years; however, at the local scale is where the impacts of seasonal weather and trends in climate become more noticeable. Across the United States, there have been large deviations from the trend line in years in which weather events have caused yield reductions

impact on local economies and local food supplies as well as world food security.

from the National Agricultural Statistics Service, www.nass.usda.gov, accessed March 8, 2018).

Projections of climate change are a result of a combined set of simulation models using various scenarios of changes in carbon dioxide (CO2) concentrations and the associated forcing functions [1]. The current CO2 concentrations are at nearly 400 ppm in 2018 and are projected to increase to a range of 794–1142 ppm by 2100 without any abatement scenarios [1]. The result of these efforts can be summarized as [1, 2]:

1. Global mean temperatures will continue to increase throughout the twenty-first century if CO2 concentrations continue to increase and under the highest emission scenario would range from 2.6 to 4.8C.

2. These temperatures changes will not be uniform across regions with increases over land surfaces being larger than over the oceans.

that disruption of the pollination process could become more likely especially with the potential for more extreme temperature events. Quantifying the impact of episodes of temperature extremes on pollen viability and the disruption of reproductive processes will become more important with the projection that extreme temperature events will increase under climate change (Tebabldi et al. [12]). These temperature ranges and the potential for extreme events will become important for corn growth and production because of the projection that temper-

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The relationship of corn phenology to temperature has been described through the use of growing degree days with a growing degree day (GDD) calculated as (Tmax + Tmin)/2 – Tbase, where Tmax is the maximum daily temperature, Tmin is the daily minimum temperature and Tbase is the temperature at which growth stops. Kumudini et al. [13] evaluated eight different thermal models for the estimation of corn phenological development. These thermal models were classified into empirical linear typical of the GDD model first shown by Gilmore and Rogers [14] with the most robust model having a Tbase of 10C and an optimum of 30C. Another class of thermal models is the empirical nonlinear model described by Brown and Bootsma [15] where the following relationships were used to estimate crop heat units (CHU): if Tmin < 4.4C then Tmin = 4.4C to derive CHUmin = 1.8(Tmin – 4.4C); if Tmax < 10C then Tmax = 10C; to derive CHUmax = 3.33(Tmax – 10C) – 0.084(Tmax – 10C)<sup>2</sup> and CHU = (CHUmax + CHUmin)/2. Stewart et al. [16] used a non-linear empirical model and separated the vegetative and reproductive stages of growth with different functions. The third class of thermal models can be classified as the process-based models similar to the thermal functions used in Agricultural Production Systems sIMulator (APSIM) as described by Wilson et al. [17] which are based on estimates of air temperature at 3 hour intervals throughout the day and given as: if T < 0C then T = 0C and if T > 44C then T = 44C and calculated for different temperature ranges as 0C=< T < 10C: IR = T(10/18C); 18C=< T < 34C: IR = T – 8C; and 34C=< T < 44C: IR = 26C – (T – 34C)2.6 and thermal units are given as ∑(IR/8), where IR = instantaneous rates or measurements. In comparing these different approaches, Kumudini et al. [13] found that the precision in terms of goodness of fit was calendar days < empirical

An application of the GDD approach was developed by Neild and Richman [18] where they combined thermal units with precipitation in an agroclimatic index to determine where different corn hybrids could be grown around the world. Currently, this type of model has been replaced with simulation models similar to APSIM [19] to determine climate impacts on corn growth and production. If the thermal units per leaf appearance rate is constant for the vegetative stage of growth then as the temperature increases there will be a more rapid accumulation of leaves in the crop. This effect as observed by Hatfield [20] and Hatfield and Prueger [21] for corn grown under climatic normal (1980–2010) for Ames, Iowa and normal +4C temperatures throughout the complete growing season for three different corn hybrids. There was no difference in the total number of leaf collars and cumulative leaf area between temperature regimes; however, there was a large difference in yield with the higher temperatures greatly reducing grain yield (Figure 4). Analysis revealed there was no difference in the GDD's for leaf collar appearance between the two temperature regimes suggesting that as temperatures increase there will be a more rapid rate of advancement in the phenological

atures will increase in the future.

linear < process-based < empirical non-linear.


These factors will affect corn growth and productivity and this chapter is directed toward showing how these changes in climate will potentially affect corn production in the future. A general summary of climate impacts on crops was prepared by Hatfield et al. [3] and reveal for corn that temperature and precipitation are the two critical factors. Since corn is a C4 plant, the response to increasing CO2 will be minimal. Leakey et al. [4] found that leaf photosynthetic response was 3% to a doubling of CO2 concentrations while total biomass and grain yield increased by 4%. They did observe that leaf stomatal conductance was decreased by 34% under these same experiments. These differences in physiological activity due to increased CO2 are small compared to C3 species and will not the most evident response to the changing climate. Therefore, in this chapter we will focus on temperature and precipitation impacts on corn.

#### 3. Phenology of corn

The phenology of corn has been described as the appearance of leaves or leaf collars during the vegetative stage and accumulation of material in the grain during the reproductive stage. The developmental stages of corn has been recently described by Abendroth et al. [5] and similar guidelines are used to quantify the phenological stage of corn during the growth cycle. What is important for assessing the effect of climate on corn is to explore what role climate variables have on corn phenology. The most critical variable in phenological development is temperature and each plant has a specific range of temperatures for growth as defined as the upper and lower limit (threshold) and an optimum [3]. For corn during the vegetative stage this has been identified as 8 to 38C with an optimum of 34C [6, 7] while the range for the reproductive stage is 8–30C [8]. Typically, the lower temperature limit in growth models has assumed to be 10C. Survival of pollen are sensitive to temperature, e.g., temperatures exceeding 35C have been proven detrimental to pollen viability [9, 10]. There is a strong interaction of temperature with vapor pressure deficit and the viability in the time of movement from the tassel to the silk has been shown to decrease with decreasing moisture content [11]. These results would suggest that as the temperature increases and vapor pressure deficit increases that disruption of the pollination process could become more likely especially with the potential for more extreme temperature events. Quantifying the impact of episodes of temperature extremes on pollen viability and the disruption of reproductive processes will become more important with the projection that extreme temperature events will increase under climate change (Tebabldi et al. [12]). These temperature ranges and the potential for extreme events will become important for corn growth and production because of the projection that temperatures will increase in the future.

2. These temperatures changes will not be uniform across regions with increases over land

3. As the global temperatures increase there will be more hot extremes and fewer cold

4. Precipitation will increase with increases in global mean surface temperature and could

and water vapor inclines. That leads to higher intensity of precipitation, i.e. higher amount

6. Annual surface evaporation will increase as the temperatures increases; however, over

These factors will affect corn growth and productivity and this chapter is directed toward showing how these changes in climate will potentially affect corn production in the future. A general summary of climate impacts on crops was prepared by Hatfield et al. [3] and reveal for corn that temperature and precipitation are the two critical factors. Since corn is a C4 plant, the response to increasing CO2 will be minimal. Leakey et al. [4] found that leaf photosynthetic response was 3% to a doubling of CO2 concentrations while total biomass and grain yield increased by 4%. They did observe that leaf stomatal conductance was decreased by 34% under these same experiments. These differences in physiological activity due to increased CO2 are small compared to C3 species and will not the most evident response to the changing climate. Therefore, in this chapter we will focus on temperature and precipitation impacts on

The phenology of corn has been described as the appearance of leaves or leaf collars during the vegetative stage and accumulation of material in the grain during the reproductive stage. The developmental stages of corn has been recently described by Abendroth et al. [5] and similar guidelines are used to quantify the phenological stage of corn during the growth cycle. What is important for assessing the effect of climate on corn is to explore what role climate variables have on corn phenology. The most critical variable in phenological development is temperature and each plant has a specific range of temperatures for growth as defined as the upper and lower limit (threshold) and an optimum [3]. For corn during the vegetative stage this has been identified as 8 to 38C with an optimum of 34C [6, 7] while the range for the reproductive stage is 8–30C [8]. Typically, the lower temperature limit in growth models has assumed to be 10C. Survival of pollen are sensitive to temperature, e.g., temperatures exceeding 35C have been proven detrimental to pollen viability [9, 10]. There is a strong interaction of temperature with vapor pressure deficit and the viability in the time of movement from the tassel to the silk has been shown to decrease with decreasing moisture content [11]. These results would suggest that as the temperature increases and vapor pressure deficit increases

; however, there will be substantial spatial variation in these changes.

. The air can take up more water,

surfaces being larger than over the oceans.

98 Corn - Production and Human Health in Changing Climate

increase 1 to 3% C<sup>1</sup>

of rainfall per rain event.

corn.

3. Phenology of corn

extremes at both daily and seasonal time scales.

5. The water holding capacity of air increases by 7% C<sup>1</sup>

land, evaporation will be linked to precipitation.

The relationship of corn phenology to temperature has been described through the use of growing degree days with a growing degree day (GDD) calculated as (Tmax + Tmin)/2 – Tbase, where Tmax is the maximum daily temperature, Tmin is the daily minimum temperature and Tbase is the temperature at which growth stops. Kumudini et al. [13] evaluated eight different thermal models for the estimation of corn phenological development. These thermal models were classified into empirical linear typical of the GDD model first shown by Gilmore and Rogers [14] with the most robust model having a Tbase of 10C and an optimum of 30C. Another class of thermal models is the empirical nonlinear model described by Brown and Bootsma [15] where the following relationships were used to estimate crop heat units (CHU): if Tmin < 4.4C then Tmin = 4.4C to derive CHUmin = 1.8(Tmin – 4.4C); if Tmax < 10C then Tmax = 10C; to derive CHUmax = 3.33(Tmax – 10C) – 0.084(Tmax – 10C)<sup>2</sup> and CHU = (CHUmax + CHUmin)/2. Stewart et al. [16] used a non-linear empirical model and separated the vegetative and reproductive stages of growth with different functions. The third class of thermal models can be classified as the process-based models similar to the thermal functions used in Agricultural Production Systems sIMulator (APSIM) as described by Wilson et al. [17] which are based on estimates of air temperature at 3 hour intervals throughout the day and given as: if T < 0C then T = 0C and if T > 44C then T = 44C and calculated for different temperature ranges as 0C=< T < 10C: IR = T(10/18C); 18C=< T < 34C: IR = T – 8C; and 34C=< T < 44C: IR = 26C – (T – 34C)2.6 and thermal units are given as ∑(IR/8), where IR = instantaneous rates or measurements. In comparing these different approaches, Kumudini et al. [13] found that the precision in terms of goodness of fit was calendar days < empirical linear < process-based < empirical non-linear.

An application of the GDD approach was developed by Neild and Richman [18] where they combined thermal units with precipitation in an agroclimatic index to determine where different corn hybrids could be grown around the world. Currently, this type of model has been replaced with simulation models similar to APSIM [19] to determine climate impacts on corn growth and production. If the thermal units per leaf appearance rate is constant for the vegetative stage of growth then as the temperature increases there will be a more rapid accumulation of leaves in the crop. This effect as observed by Hatfield [20] and Hatfield and Prueger [21] for corn grown under climatic normal (1980–2010) for Ames, Iowa and normal +4C temperatures throughout the complete growing season for three different corn hybrids. There was no difference in the total number of leaf collars and cumulative leaf area between temperature regimes; however, there was a large difference in yield with the higher temperatures greatly reducing grain yield (Figure 4). Analysis revealed there was no difference in the GDD's for leaf collar appearance between the two temperature regimes suggesting that as temperatures increase there will be a more rapid rate of advancement in the phenological

conditions owing to reduced pollen viability as impacted by increased temperatures. A critical knowledge gap under future climate scenarios will be to evaluate the interaction of high temperature and increased humidity on pollen survivability and the efficiency of the pollination process. Lobell and Field [25] found maize yields decreased 8.3% per 1C rise without any additional effect due to water stress which was confirmed by Mishra and Cherkauer [26] for Midwest corn grain yields. Challinor et al. [27] compiled a meta-analysis of over 1700 published simulations for wheat (Triticum aestivum L.), rice (Oryza sativa L.), and corn. They found that without implementing adaptation strategies there would be a loss in yield in both temperate and tropical regions with only 2C of warming. They also found that adaptation practices could increase simulated yields by 7–15% with this same temperature increase; however, the practices were more effective in wheat and rice than for corn. There was consensus among the simulation models that yield decreases were be greater in the second half of the century with the greater declines in the tropical areas compared to the temperate regions. They estimated that corn yields would decrease by nearly 15% in temperate regions with a 4C

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increase and no adaptation but showed no decrease with adaptation practices [27].

water.

Temperature and precipitation interact to affect corn productivity. Short-term water deficits and drought reduce growth and grain yield and are often the largest cause of crop losses. In the United States, drought was related to 41% of crop losses, while excess water was attributed to 16% of the yield loss [28]. Drought stress during the early and middle reproductive stages affected grain yields and these phenological stages were found to be the most sensitive to water stress [29]. Increases in spring precipitation can cause yield reductions due to aeration stress caused by flooded soils; however, drought stress remained the primary factor linked with reduced grain production [29]. In rainfed environments where corn is primarily grown, temperature and precipitation changes under climate change will negatively impact grain production and these interactions need to be more fully understood. In an analysis of wheat production in Europe, Semenov et al. [30], stated that understanding of the effects of higher temperatures and drought stresses during the booting and flowering periods would potentially lead to adaptation practices with the potential to reduce losses in grain numbers and grain weight. With both short-term water stress and drought as major factors affecting grain yield, improved water availability through more extensive root system and changes in root architecture would benefit yield stability [31]. The excess soil moisture in the root zone will require improved soil structure to facilitate gas exchange between the root system and the atmosphere [32]. The impact of precipitation is a combination of the precipitation amount and the soil water holding capacity. This was illustrated in an analysis by Egli and Hatfield [33] where they found average county level corn yields were a function of the soils ability to supply

Evaluation of corn yield response to climate is complex because of the interactions of the impacts of temperature and precipitation. To provide a more robust framework for evaluating yield response the utilization of the yield gap as the difference between potential yield and actual yield has been utilized ([34]; van Bussel et al. [35]). This concept has been discussed and utilized for several decades but recently has been extended to create a yield gap atlas for the world. The yield gap approach allows for a quantitative assessment of the ability of the crop to achieve its potential yield and the inability of closing the yield gap can often be ascribed to

Figure 4. Differences in total leaf collars, cumulative leaf area, and grain yield of three corn hybrids grown under normal Ames, Iowa temperatures and normal +4C temperatures. (data redrawn from [20]).

development with no effect on the size of the corn plant at the end of the vegetative stage. There was a large difference in grain yield between temperature regimes with a faster rate of maturity with a subsequent reduction in grain production.
