Yield

Current global yields are presented in Table 6.1. To predict how these will change with global atmospheric and climatic change, we are limited almost entirely to model estimates. These are predominantly empirical and depend on predicting beyond our experience, particularly with respect to interactions for which few experiments have been conducted. Because of the difficulty of containing pCO2, experimentation has been limited to glasshouses and small open-top chambers. Whilst these provide an indication of direction of response and potential interactions, they are not suited to predicting absolute changes (McLeod and Long, 1999). Predicting crop yields in the future is rather like betting on a horse in a race, with all its uncertainties and potential surprises and with the added handicap of only having seen the horse move in its box and never on the race course. Morison and Lawlor (1999) have recently highlighted how many of the limited studies of the interactive effects of rising pCO2 and temperature on crop production and yield have shown changes in production that contradict model expectations. This highlights the need for increased understanding of the mechanisms underlying these interactions in controlled environments and advancing systems for realistic field evaluation at multiple sites.

Technology exists to examine how crops will respond to elevated pCO2 in the open air via free air carbon dioxide enrichment (FACE) experiments (McLeod and Long, 1999), or how elevated pCO2 and temperature will interact via advanced climate-controlled glasshouses or gradient tunnels (Morison and Lawlor, 1999). The expense of such facilities seems to have deterred the development of any significant network to adapt and test the models. This will be essential for providing adequate guidance for managing future world food supplies and to start selecting or developing genotypes for these changed conditions. Regional climatic responses to a doubling of atmospheric pCO2 will vary significantly (Watson et al, 1998). Crop yields are likely to be even more variable and difficult to predict, because they depend on complex interactions among plant physiological processes, weather and the soil environment, which can be subject to extensive agronomic modification (Brown and Rosenberg, 1997). These interactive processes determine plant photosynthesis and respiration, water use, growth and phenology, all of which impact plant yield. Reported enhanced growth under elevated pCO2 in C4 species (see above) has generally been attributed to increased WUE. However, there are reports of photosynthetic stimulation of C4 under elevated pCO2, although this enhancement may be limited to conditions where elevated pCO2 alleviates mild drought stress (Samarakoon and Gifford, 1996). Overall predictions of maize and sorghum yields suggest a reduction in areas where temperatures are currently optimal (i.e. southern and central USA and Southern China, and much of sub-Saharan Africa) and an increase in areas where temperatures are suboptimal (i.e. northern USA, the European Union and northern China).

Models generally assume non-limiting water and nutrients and no change in agronomic practices (Houghton et al., 1996; Wang and Erda, 1996; Brown and Rosenberg, 1997; Buan et al., 1996). Elevated pCO2 is generally assumed to have little or no effect on yield. This assumption seems increasingly flawed, particularly for rain-fed crops (Samarakoon and Gifford, 1996).

Brown and Rosenberg (1997) simulated crop yield with the Erosion Productivity Impact Calculator (EPIC) for five representative farms in the central USA. The individual and combined effects of a range of environmental and physiological factors were used to predict yields of rain-fed sorghum in Nebraska, wheat in Kansas, maize in Missouri and Iowa, and of irrigated maize in Nebraska. Single factor effects on crop yield (Fig. 6.3) varied between irrigated and rain-fed maize and rain-fed sorghum. In all cases, increase in temperature decreased yield by shortening the duration of growth, whilst increase in pCO2 increased predicted yield. Reductions in solar radiation, humidity and (with the exception of irrigated maize) precipitation resulted in reduced crop yields, the magnitude of these reductions varying between crops.

Though modelling provides useful insight into the potential effects of a range of single factors on yield, actual yields will be determined by interaction among these and other variables. Brown and Rosenberg (1997) modelled interactive effects in 16 cases, which included elevation of pCO2 to 45 Pa (C450) and 55 Pa (C550) (Fig. 6.3). In isolation, elevated pCO2 increased yield of rain-fed crops, but when this was combined with the other expected changes in climate the net result was a decrease in yield of 2-35% for Missouri rain-fed maize and 3-15% for Nebraska irrigated maize. Increased yields of 6-16% for Iowa maize and of 23-37% for Nebraska sorghum were predicted for scenarios which included increased pCO2 and precipitation together with reduced solar radiation. Generally, for all five crops examined, reductions in yield resulting from increased temperature were to some extent mitigated by elevated pCO2 and increased precipitation. Mitigation was most pronounced in sorghum. Yield reductions in this region may be smaller if adaptation of cultivation is taken into account. Simulation studies predicted that changes in agronomic practices such as earlier planting of longer-season cultivars and moisture conservation measures could offset some of the yield losses induced by climatic change in maize, in the region of Missouri, Iowa, Nebraska and Kansas (Easterling et al., 1992).

Fig. 6.3. Percentage alteration of yield from the baseline climate of 1951 to 1980 to changes in individual climatic variables: (a) Missouri rain-fed maize; (b) Nebraska irrigated maize; (c) Nebraska rain-fed sorghum. T = temperature + 3°C; P = precipitation; SR = solar radiation; VP = vapour pressure; C = CO2 (Pa x 10); Rs = stomatal resistance; LAI = leaf area index. (Brown and Rosenberg, 1997.)

Fig. 6.3. Percentage alteration of yield from the baseline climate of 1951 to 1980 to changes in individual climatic variables: (a) Missouri rain-fed maize; (b) Nebraska irrigated maize; (c) Nebraska rain-fed sorghum. T = temperature + 3°C; P = precipitation; SR = solar radiation; VP = vapour pressure; C = CO2 (Pa x 10); Rs = stomatal resistance; LAI = leaf area index. (Brown and Rosenberg, 1997.)

Wang and Erda (1996) considered the impact of climatic change and variability on simulated maize production in China. The CERES-Maize model was run for 35 sites that were representative of the main maize-growing regions. Simulated yields at most sites were reduced, primarily as a result of the reduced growth and grain-filling periods. In a few northern sites, simulated yields increased because maize growth at these higher latitudes is currently temperature-limited. Similar increases have been predicted for the northern edge of the North American corn belt. Singh et al. (1998) suggested that a twice-normal CO2 climate would increase maize and sorghum yields in Quebec by 20% and decrease wheat and soybean yields by 20-30%. Wang and Erda (1996) noted the critical point that these models made assumptions that were likely to result in an overestimation of yield. This identifies once more the need for models that correctly simulate the effect of climate factors and soil on crop responses, including yield. They conclude that at present these model results should not be regarded as predictions, but rather as plausible assessments of the potential direction of climatic change-induced changes in maize production.

Although rice is the principal crop throughout most of tropical Asia, maize is an important secondary crop in many countries, particularly the Philippines, where the yield is about half that of rice (Watson et al., 1998). The vulnerability of rice and corn to climatic change in the Philippines was assessed by applying the predicted climate change for a doubling of atmospheric pCO2 from four general circulation models (GCMs) (Table 6.3) (Buan et al., 1996). The effects

Table 6.3. Predicted change in yield of two corn hybrids for selected climatic change scenarios for three study sites (ISU, Isabela State University; CMU, Central Mindanao University; USM, University of Southern Mindanao) in the Philippines, using the CERES-Corn model. GCM models: CCCM = Canadian Climate Centre Model; GFDL = Geophysical Fluid Dynamics Laboratory model; GISS = Goddard Institute for Space Studies model; UKMO = United Kingdom Meteorological Office model. (Buan et al, 1996.)

Percentage changes in yield

Corn Cropping Yield base-

Study sites varieties season (t ha-1) CCCM GFDL GISS UKMO

Table 6.3. Predicted change in yield of two corn hybrids for selected climatic change scenarios for three study sites (ISU, Isabela State University; CMU, Central Mindanao University; USM, University of Southern Mindanao) in the Philippines, using the CERES-Corn model. GCM models: CCCM = Canadian Climate Centre Model; GFDL = Geophysical Fluid Dynamics Laboratory model; GISS = Goddard Institute for Space Studies model; UKMO = United Kingdom Meteorological Office model. (Buan et al, 1996.)

Percentage changes in yield

Corn Cropping Yield base-

Study sites varieties season (t ha-1) CCCM GFDL GISS UKMO

ISU

P3228

1st

6.7

-11.1

-8.6

-13.1

-5.8

2nd

5.4

-3.7

0.4

-11.2

-3.0

SWEET

1st

5.6

-10.5

-8.9

-11.4

-6.8

2nd

4.9

-7.9

-4.7

-17.7

-9.2

CMU

P3228

1st

9.5

-11.4

-8.4

-13.1

-12.7

2nd

8.0

-1.4

4.7

-7.2

2.8

SWEET

1st

8.5

-11.7

-9.0

-12.3

-12.4

2nd

7.4

-8.4

-1.8

-15.1

-2.0

USM

P3228

1st

7.1

-15.3

-17.9

-17.8

-14.6

2nd

6.9

-16.1

-16.1

-17.3

-8.1

SWEET

1st

6.0

-15.9

-22.9

-18.4

-15.9

2nd

5.6

-18.2

-18.7

-18.2

-6.6

MEAN

6.8

-11.0

-9.3

-14.4

-7.8

of climatic change on crop productivity were simulated using the CERES-Com model from Decision Support System for Agrotechnology Transfer version 3 (DSSAT 3). All GCMs indicated the same trends in temperature, but varied in their estimates for rainfall and solar radiation. The Canadian Climate Centre Model predicted a slight decrease in solar radiation, while other models predicted slight increases. Estimates for changes in rainfall were much more varied. For example, for the first cropping at Isabela State University, the Geophysical Fluid Dynamics Laboratory model predicted a 24.6% increase, whilst the Goddard Institute for Space Studies model predicted a 27.6% decrease. Despite these differences, a reduction in maize yield was predicted for all climate change scenarios (Table 6.3). This reduction results largely from a temperature-induced reduction in the growth period. As rainfall is generally high, a reduction in rainfall of 10% would not affect the water requirement significantly; however, an increase by the same magnitude could affect yield significantly through the effects of flooding. This could be exacerbated by decreased transpiration at elevated pCO2.

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