5.3.3.4. Response of Plant Crops and Possible Adaptation Options

Very little work has investigated prospects for natural adaptation of crop species to climate change, and the results of the few studies that do have been inconclusive. However, there appears to be a wide range of resistance to high-temperature stress within and among crop species. For example, moderately large genetic variation in the tolerance to high-temperature induced spikelet sterility has been reported among and between indica- and japonica-type rice genotypes (Matsui et al., 1997). Some rice cultivars have the ability to flower early in the morning, thereby potentially avoiding the damaging effects of higher temperatures later in the day (Imaki et al., 1987).

Prospects for managed genetic modification appear to be more optimistic than for natural adaptation. Intraspecific variation in seed yield of soybean in response to elevated CO₂ was observed by Ziska et al. (1998). Differences in carbon partitioning among soybean cultivars may influence reproductive capacity and fecundity as atmospheric CO₂ increases, with subsequent consequences for future agricultural breeding strategies (Ziska et al., 1998). However, no significant intraspecific variability in responses to elevated CO₂ was detected in studies with wheat and temperate forage species (Lüscher and Nösberger, 1997; Batts et al., 1998). To promote adaptation to an environment of high CO₂ and high temperature, plant breeders have suggested selection of cultivars that exhibit heat tolerance during reproductive development, high harvest index, small leaves, and low leaf area per unit ground (to reduce heat load) (Hall and Allen, 1993). However, prospects to improve adaptation of crop species to elevated CO₂ remain very uncertain, and more research in this direction is required.

5.3.4.1. Modeling Crop Yield Impact

The number of studies that model the yield impacts of climate change (with and without CO₂ direct effects and with and without adaptation) across individual sites in regions has continued to grow since the SAR. Of particular note is the expansion of studies that explicitly model the effects of change in climate variability and means simultaneously versus change in climate means only (Southworth et al., 1999), use transient climate change scenarios, and report modeling of agronomic and socioeconomic adaptation. A selection of major global and regional model-based studies reported since the SAR is summarized in Table 5-4.

Table 5-4 yields are reported as ranges of percentage change over the climate change scenarios, modeling sites, and crop as noted. Thirteen of the yield ranges—without adaptation—are from studies of tropical crops. Of the 13 ranges, 10 encompass changes that are exclusively lower than current yields. In three ranges, a portion of the range is approximately no different from current yields or slightly above. In the tropics, most crops are at or near theoretical temperature optimums, and any additional warming is deleterious to yields. Thirty ranges of percentage changes in temperate crop yields also appear in Table 5-4. Of these 30 ranges, six encompass changes that are exclusively higher than current yields. In another seven, half or more of the changes were more than current yields. In yet another seven, less than half of the changes extended above current yields. The remaining 10 ranges encompassed changes that were exclusively less than current yields. Hence, in two-thirds of the cases, temperate crop yields benefited at least some of the time from climate change.

New work on climate change scenarios (Mitchell et al., 2000) generated with stabilized radiative forcing at 550 and 750 ppm equivalent-CO₂ and unstabilized radiative forcing (i.e., unmitigated emissions) in the HadCM2 model simulated major cereal yield response globally in 2080 (Arnell et al., 2001). The pattern of yield changes with unstabilized forcing duplicates the pattern described above: Generally positive changes at mid- and high latitudes overshadowed by reductions in yields at low latitudes. Stablization at 550 ppm ameliorates yield reductions everywhere, although substantial reductions persist in many low-latitude countries. Stabilization at 750 ppm produces a pattern of yield response that is intermediate relative to the 550 ppm and unstabilized forcing scenarios, with anomalous yield increases in mid-latitudes relative to 550 ppm as a result of interactions between atmospheric CO₂, temperature, and moisture. More studies are needed before confidence levels can be assigned to understanding of the agricultural consequences of stabilization, although this work is an important step.

In all agricultural regions, the effects of natural climate variability are likely to interact with human-induced climate change to determine the magnitude of impacts on agricultural production. Some analyses postulate an increase in weather variability (Mearns et al., 1992, 1995; Rosenzweig et al., 2000); simulations of wheat growth indicate that greater interannual variation of temperature reduces average grain yield (Semenov and Porter, 1995). Hulme et al. (1999) simulated natural climate variability in a multi-century control climate for comparison with changed variability in a set of transient climate change simulations. Wheat yields were simulated with control and climate change scenarios. For some regions, the impacts of climate change on wheat yields were undetectable relative to the yield impacts of the natural variability of the control climate (see Table 5-4). Greater efforts to take account of the "noise" of natural climate variability are indicated (Semenov et al., 1996).

The importance of diurnal climate variability has emerged since the SAR (Reilly et al., 1996). Cold temperatures presently limit the yield of rice in all temperate rice-growing regions. Jacobs and Pearson (1999) provide new field results on irreversible effects and retardation (but recoverable) impacts of cold temperatures on various physiological processes in rice. On the other hand, rice spikelet sterility above 35°C at flowering (usually during daytime) puts rice at risk from increased daily maximum temperatures (Horie et al., 1996). In light of recent observed rises in temperatures that are larger for daily minima than daily maxima (Easterling et al., 1997), Dhakhwa et al. (1997) and Dhakhwa and Campbell (1998) conclude that, compared to equal day-night warming, differential warming leads to less water loss through evapotranspiration and better WUE. This is likely to lead to enhanced photosynthesis, crop growth, and yield—although at a possible loss of nutritional quality (Murray, 1997). Possible reduction of frost incidence is not normally considered in these studies. On the negative side, higher nighttime temperatures could extend the overwintering range for some insect pests and broaden the range of other temperature-sensitive pathogens.

Substantial progress has been made in development of transient (time-evolving) scenarios of climate change for use in agricultural impact assessment. An important question arises regarding whether 2 years with exactly the same climate, one produced by a transient scenario and the other by an equilibrium scenario, would give different production system responses. Many crop models contain cumulative functions that retain environmental information over several years (e.g., water balance, soil nutrients). This factor alone could account for substantial yield response differences between transient and equilibrium climate change scenarios. Only a few studies deliberately have compared simulated yields with transient and equilibrium climate change scenarios. Using the UKHIV equilibrium scenario with increased interannual variability at Rothamsted, Semenov et al. (1996) simulate a loss of wheat yield relative to current with two crop models and no change with a third. With the UKTR transient scenario, all three models show yield increases relative to current climate. The U.S. Country Studies Program (Smith et al., 1996a) used the Clouds and Earth's Radiant Energy System (CERES) model to simulate larger average increases in winter wheat across Kazakhstan with the GFDL transient climate change scenario (for the 10th decade) (+21% winter wheat yield) than the GFDL equilibrium scenario (+17% winter wheat yield). Spring wheat yields decreased with both scenarios; again, however, yields simulated with the transient climate change were not as adversely affected as those simulated with the equilibrium climate change. Rosenzweig and Iglesias (1998) also found that wheat, maize, and soybean yields are less adversely affected by transient climate change than equilibrium climate change. Lack of consistency in application of transient climate change scenarios to impact modeling between studies results in competing explanations about differences in impact estimates between the two types of climate change scenarios.

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