Challenges for Research

Contact Information

Jerry L. HatfieldLaboratory Director National Laboratory for Agriculture and the

EnvironmentDirector, Midwest Climate Hub2110 University BlvdAmes, Iowa 50011515-294-5723515-294-8125 (fax)jerry.hatfield@ars.usda.gov

Framework For Agronomic

Systems

Inputs

Climate

Soil

Genetics

Nutrients

Water

Cropping

Systems

Corn-

Beans

Wheat-

Sunflower

Cotton-

Sorghum

Outputs

Grain

Forage

Env. Goods

Nitrate

Sediment

GHG’s

Mitigation Strategies Adaptation Strategies

Climate Factors

Inputs

Temperature

Precipitation

Solar radiation

Carbon dioxide

Direct

Growth

Phenology

Yield

Indirect

Insects

Diseases

Weeds

Soil is the underlying factor as a

resource for nutrients and water

Climate vs Weather

Climate determines where we grow a

crop

Weather determines how much we

produce

Maize Yields

Maize Production

Year

1960 1970 1980 1990 2000 2010

Gra

in Y

ield

(M

g h

a-1

)

0

2

4

6

8

10

12

United States

Mexico

China

Wheat Yields

Wheat Grain Production

Year

1960 1970 1980 1990 2000 2010

Gra

in Y

ield

(M

g h

a-1

)

0

1

2

3

4

5

6

United States

Mexico

China

Projections“Assuming no change in population growth, food consumption patterns and food

waste management, the following production increases must take place by 2050:

cereals production must increase by 940 million tonnes to reach 3 billion tonnes;

(45% increase)

meat production must increase by 196 million tonnes to reach 455 million

tonnes; (77% increase)

and oilcrops by must increase by 133 million tonnes to reach 282 million tonnes

(89% increase) (Alexabdratos and Bruinsma, 2012).

It is also estimated that global demand for crop calories will increase by 100

percent ±11 percent and global demand for crop protein will increase by 110

percent ±7 percent from 2005 to 2050 (Tilman et al. 2011). “

Alexandratos N, Bruinsma J. 2012. World agriculture towards 2030/2050, the 2012

revision. ESA Working Paper No. 12-03, June 2012. Rome: Food and Agriculture

Organization of the United Nations (FAO). (Available from

http://www.fao.org/docrep/016/ap106e/ap106e.pdf)

Tilman D, Balzer C, Hill J, Befort BL. 2011. Global food demand and the sustainable

intensification of agriculture. PNAS 108(50):20260–20264. Washington DC:

Proceedings of the National Academy of Sciences of the United States of America.

(Available from http://www.pnas.org/content/108/50/20260)

World Soybean Production

World Soybean Production

Year

1960 1970 1980 1990 2000 2010 2020

Yie

ld (

bu/A

)

15

20

25

30

35

40

45

Data points

Yield = -789.79 + 0.41 yr r2 = 0.95

By 2050, we will

have a 1066 kg/ha

deficit in

production

compared to

projected

requirements

Corn Grain Production

World Corn Production

Year

1960 1970 1980 1990 2000 2010 2020

Yie

ld (

bu/A

)

20

30

40

50

60

70

80

90

Data points

Yield = -1979.659 +1.02 yr r2 = 0.97

By 2050, we

have a 125

kg/ha deficit on

expected

production

compared to

required

production

Wheat Grain Production

World Wheat Production

Year

1960 1970 1980 1990 2000 2010 2020

Yie

ld (

bu

/A)

15

20

25

30

35

40

45

50

55

Data points

Yield = -1233.819 + 0.639 yr r2 = 0.98

By 2050, we

have a 627.2

kg/ha excess in

production

estimates

compared to

projected

requirements

Brazil Wheat

Brazil Wheat

Year

1960 1970 1980 1990 2000 2010 2020

Yie

ld (

kg

ha

-1)

0

500

1000

1500

2000

2500

3000

Data points

Yield = -68839.61 + 35.35 Year r2=0.80

Brazil Soybean

Brazil Soybean

Year

1960 1970 1980 1990 2000 2010 2020

Yie

ld (

kg h

a-1

)

500

1000

1500

2000

2500

3000

3500

Data points

Yield = -72874.7 + 37.62 Year r2=0.89

Climate Factors

Inputs

Temperature

Precipitation

Solar radiation

Carbon dioxide

Direct

Growth

Phenology

Yield

Indirect

Insects

Diseases

Weeds

Soil is the underlying factor as a

resource for nutrients and water

Carbon Dioxide Increases

Present vs. Past

L. Ziska, USDA-ARS

Present vs. Future

L. Ziska, USDA-ARS

Carbon Dioxide-Water

Interactions

Two levels of CO2 and three soil

water levels on soybean

CO2 and Temperature

Interactions

CO2 and temperature effects offset each other in a well-watered

situation; however, in water limited the positive effect of CO2 is

dominant

Temperature Responses

Difference in temperature response between the vegetative and reproductive

stage of development for crops. The higher the temperature the faster the rate

of development

Temperature

Crop

Optimum Temp (C)

Temp Range

(C)

Failure

Temp

(C)Veg Reprod Veg Reprod

Maize 34 18-32 18-22 35

Soybean 30 26 25-37 22-24 39

Wheat 26 26 20-30 15 34

Rice 36 33 33 23-26 35-36

Cotton 37 30 34 25-26 35

Tomato 22 22 22-25 30

Nighttime Temperatures

Impact of Warm Nights on Corn

and Soybean Productivity

Corn and Soybean Production Fields

Average Minimum Temperature (C)

8 10 12 14 16 18 20 22 24 26

Net C

arb

on F

lux (

mg m

-2 s

-1)

3.5

4.0

4.5

5.0

5.5

6.0

6.5

7.0

Corn

Soybean

Temperature effects on Corn

Phenology

Corn Hybrid RX730

Days after Planting

0 20 40 60 80 100 120

Tota

l C

olla

rs

0

5

10

15

20

25

Normal Temperatures

Warm Temperatures

Corn Hybrid DK 61-72

Days after Planting

0 20 40 60 80 100 120

Tota

l C

olla

rs

0

5

10

15

20

25

Normal Temperatures

Warm Temperatures

Corn Hybrid XL45A

Days after Planting

0 20 40 60 80 100 120

Tota

l C

olla

rs

0

5

10

15

20

25

Normal Temperatures

Warm Temperatures

Rhizotron study with warm chamber 4C warmer than normal

chamber with simulation of Ames IA temperature patterns.

1505 15805 5519 19130 4453 24774 kg ha-1

Rhizotron ResultsY

ield

(g

/pla

nt)

Soil Water Levels Soil Water Levels

0.5 1.0 1.5 0.5 1.0 1.5

Normal Temp High Temp (reprod)

0

10

20

30

40

50

60

70

80

90

100

Combinations of water

and temperature

stresses cause

disruption in pollination

and grain-fill

Current Reductions in Yields

Lobell et al. 2011 Science 333:616-620

Current Mega-climate regimes

Future (2050) mega-

climate regimes

Move from a favorable to

unfavorable climate for

wheat

Ortiz et al. Agric Ecosys &

Environ. 2008. 126:46-58

Temperature Effects on

Evaporation

Air Temperature (C)

0 10 20 30 40 50

Satu

ratio

n V

ap

or

Pre

ssu

re (

kP

a)

0

2

4

6

8

10

12

14

e* = 0.61121 exp(17.502Ta/Ta + 240.97)

𝐸𝑇 =𝜌𝑐𝑝(𝑇0 − 𝑇𝑠)

𝑟𝑎+

𝜌𝑐𝑝[𝑒𝑠 𝑇0 − 𝑒𝑎]

𝛾(1 + 𝑟𝑠

𝑟𝑎)𝑟𝑎

Global Models Disagree on CO2 (Climate) Effect on ET

Response for future

RCP 8.5 HadGEM-ES:

Solid - CO2 rising

Dashed - no CO2

Global gridded

models (ISI-MIP)

vary in ET response

to climate change.

Soil Water Use Rates

C orn W ater U se 2000

D ay of Year

100 120 140 160 180 200 220 240 260 280

Wa

ter

Us

e (

mm

)

0

100

200

300

400

500

600

C larion Spring N (100 kg/ha)

W ebster Spring N (100 kg/ha)

C larion Fall N (200 kg/ha)

W ebster Fa ll N (200 kg/ha)

Crop Yield Variation

Precipitation

Expect increased variation among years

Expect increased variation within a year

Expect increase in intensity of storms

and decreased frequency of storms

Soil Water Availability

Organic Matter (%)

0 1 2 3 4 5 6 7

Ava

ilab

le W

ate

r C

on

ten

t (%

)

0

5

10

15

20

25

30

35

Data Points

Sand, AWC = 3.8 + 2.2 OM

Silt Loam, AWC = 9.2 + 3.7 OM

Silty clay loam, AWC = 6.3 + 2.8 OM

Hudson, 1994

Variation in Yields

Iowa County Maize Yields

Fraction of Potential Maize Yield

0.2 0.4 0.6 0.8 1.0 1.2

Fre

quency

0

5

10

15

20

25

30

Cass County

Floyd County

Story County

Washington County

The majority of the yield losses due to the weather are short-term stresses

20% of the yield

loss occurs 80%

of the time due

to water

availability

NCCPI-AG

0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Co

un

ty Y

ield

(g

m-2

)

180

200

220

240

260

280

300

320

340

Kentucky

Iowa

Nebraska

Kentucky (Double crop)

Soybean yields across the

Midwest

NCCPI-AG

0.4 0.6 0.8 1.0

Mean

Co

un

ty Y

ield

(g

m-2

)

500

600

700

800

900

1000

Kentucky

IowaY = 436.096 + 478.149X, r2 = 0.58***

Maize County Yields

Implications

Climate will definitely impact crops both directly and indirectly

Soil management to increase water holding capacity and reduce E from ET will be a critical climate resilient factor

Quantify the indirect effects due to insects, diseases, and weeds

Quantify the effects of climate change on nutritional quality of grain, forage, and produce

We need to approach climate resilience and adaptation strategies as a G x E x M problem