Page 140 - Climate Change and Food Systems

climate change and food systems: global assessments and implications for food security and trade
risk, particularly in regions where crop cultivation is currently limited by low temperatures (Trnka et al., 2011, 2014; Rötter et al., 2013a). On the other hand, higher temperatures during sensitive crop growth stages can cause heat stress, which can have various effects (and, as mentioned above,
is still only incorporated in a few crop simulation models). For example, temperature thresholds
of 32-36 °C for a few hours around flowering (threshold depending on crop/crop cultivar) may strongly affect floret mortality/spikelet fertility, resulting in yield damages and losses, dependent on the frequency and intensity of the stress – as has been reported for wheat, groundnut, sunflower, maize and rice (Porter and Gawith, 1999;
Challinor et al., 2005, Moriondo et al., 2011b; Teixeira et al., 2012; Sanchez et al., 2014; Matsui, 1997; Wheeler et al., 2000). In the case of cereals like wheat it has been found that heat stress with maximum temperatures above certain thresholds – e.g. above 34 °C – accelerates leaf senescence and hence hastens maturity even more than the mean temperature effect on phenology alone (Asseng et al., 2011). Elevated temperatures also increase the vapour pressure deficit between air and leaf, which leads to increased transpiration rates and causes a decline in water-use efficiency (Ray et al., 2002). Furthermore, crops respond to very high vapour pressure deficit by closing their stomates, with the effect that net photosynthesis is reduced. Finally, warmer temperatures can stimulate or negatively affect photosynthesis, depending on the crop-specific temperature optimum and current temperature regime (Porter and Semenov, 2005; Sanchez et al., 2014).
Precipitation
Changes in precipitation can be either positive
or negative, depending on the current weather regime and the extent and direction of the change. Increased precipitation can reduce drought-related production risks in areas that suffer from water stress under current conditions. On the other hand, too much rainfall can degrade soil conditions by reducing the soil oxygen content. Moreover, the projected increase of precipitation, such as during
winter and spring in northern latitudes, is expected to substantially increase nitrogen leaching, surface runoff and soil erosion from agricultural fields; this has been shown, for example, in the simulations of Eckersten et al. (2001).
CO2 concentration
Increased atmospheric CO2 concentration affects crop growth and biomass accumulation in two ways. First, it enhances the CO2 fixation rate of C3 crops, with the effect that photosynthesis and therefore biomass accumulation are stimulated. Second, elevated ambient CO2 reduces stomatal conductance in both C3 and C4 crops (see chapter 2 section 2.a for a definition of C3/C4 crop types), which leads to a lower transpiration rate and therefore increased water-use efficiency (Ainsworth and Long, 2005). Due to the CO2 fertilization effect, yields of C3 and C4 crops
are expected to increase by 10-20 percent and 0-10 percent, respectively (Ainsworth et al., 2004; Gifford, 2004; Long et al., 2004) and at about 550 ppm CO2 concentration, production of aboveground biomass in pastures is expected to increase by 10 percent (Nowak et al., 2004).
Agrotechnology
Improvements in management and technology have increased crop productivity markedly over the last half of the twentieth century (see also Section 3.1). Lobell and Gourdij (2012) showed that yields of major crops have risen fairly linearly at the global scale, mainly as a result of optimizing nitrogen fertilizer input, more effective weed and disease control, extended irrigation and crop cultivar improvements through breeding. The remaining question is whether this trend will continue.
With a few exceptions (e.g. Sacks and Kucharik, 2011; Palosuo et al., 2013; Tao and Zhang, 2013b), crop simulation modelling has
not yet been applied to systematically analyse
the effect of technology change on historical yield trends or to project future yields. According to Matthews et al. (2013), crop modelling could make a substantial contribution in numerous areas. For
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