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1 2 3 4 5 Mean local temperature change (°C)

1 2 3 4 5 Mean local temperature change (°C)

Figure 5.2. Sensitivity of cereal yield to climate change for maize, wheat and rice, as derived from the results of 69 published studies at multiple simulation sites, against mean local temperature change used as a proxy to indicate magnitude of climate change in each study. Responses include cases without adaptation (red dots) and with adaptation (dark green dots). Adaptations+ represented in these studies include changes in planting, changes in cultivar, and shifts from rain-fed to irrigated conditions. Lines are best-fit polynomials and are used here as a way to summarise results across studies rather than as a predictive tool. The studies span a range of precipitation changes and CO2 concentrations, and vary in how they represent future changes in climate variability. For instance, lighter-coloured dots in (b) and (c) represent responses of rain-fed crops under climate scenarios with decreased precipitation. Data sources: Bachelet and Gay, 1993; Rosenzweig and Parry, 1994; El-Shaer et al., 1997; Iglesias and Minguez, 1997; Kapetanaki and Rosenzweig, 1997; Matthews et al., 1997; Lal et al., 1998; Moyaet al., 1998; Winters et al., 1998; Yates and Strzepek, 1998; Brown and Rosenberg, 1999; Evenson, 1999; Hulme et al., 1999; Parry et al., 1999; Iglesias et al., 2000; Saarikko, 2000; Tubiello et al., 2000; Bachelet et al., 2001; Easterling et al., 2001; Kumar and Parikh, 2001; Aggarwal and Mall, 2002; Alig et al., 2002; Arnell et al., 2002; Chang, 2002; Corobov, 2002; Cuculeanu et al., 2002; Mall and Aggarwal, 2002; Olesen and Bindi, 2002; Parry and Livermore, 2002; Southworth et al., 2002; Tol, 2002; Tubiello and Ewert, 2002; Aggarwal, 2003; Carbone et al., 2003; Chipanshi et al., 2003; Izaurralde et al., 2003; Jones and Thornton, 2003; Luo et al., 2003; Matthews and Wassmann, 2003; Reilly et al., 2003; Rosenberg et al., 2003; Tan and Shibasaki, 2003; Droogers, 2004; Faisal and Parveen, 2004; Adejuwon, 2005; Branco et al., 2005; Butt et al., 2005; Erda et al., 2005; Ewert et al., 2005; Fischer et al., 2005b; Gbetibouo and Hassan, 2005; Gregory et al., 2005; Haque and Burton, 2005; Maracchi et al., 2005; Motha and Baier, 2005; Palmer et al., 2005; Parry et al., 2005; Porter and Semenov, 2005; Sands and Edmonds, 2005; Schröter et al., 2005; Sivakumar et al., 2005; Slingo et al., 2005; Stigter et al., 2005; Thomson et al., 2005a, 2005b; Xiao et al., 2005; Zhang and Liu, 2005; Zhao et al., 2005; Aggarwal et al., 2006.

composition partly through changes in the pattern of seedling recruitment (Edwards et al., 2001). For sown mixtures, the TAR indicated that elevated CO2 increased legume development. This finding has been confirmed (Luscher et al., 2005) and extended to temperate semi-natural grasslands using free air CO2 enrichment (Teyssonneyre et al., 2002; Ross et al., 2004). Other factors such as low phosphorus availability and low herbage use (Teyssonneyre et al., 2002) may, however, prevent this increase in legumes under high CO2.

How to extrapolate these findings is still unclear. A recent simulation of 1,350 European plant species based on plant species distribution envelopes predicted that half of these species will become classified as 'vulnerable' or 'endangered' by the year 2080 due to rising temperature and changes in precipitation (Thuiller et al., 2005) (see Chapter 4). Nevertheless, such empirical model predictions have low confidence as they do not capture the complex interactions with management factors (e.g., grazing, cutting and fertiliser supply).

New Knowledge: Changes in forage quality and grazing behaviour are confirmed.

Animal requirements for crude proteins from pasture range from 7 to 8% of ingested dry matter for animals at maintenance up to 24 % for the highest-producing dairy cows. In conditions of very low N status, possible reductions in crude proteins under elevated CO2 may put a system into a sub-maintenance level for animal performance (Milchunas et al., 2005). An increase in the legume content of swards may nevertheless compensate for the decline in protein content of the non-fixing plant species (Allard et al., 2003; Picon-Cochard et al., 2004). The decline under elevated CO2 (Polley et al., 2003) of C4 grasses, which are a less nutritious food resource than C3 (Ehleringer et al., 2002), may also compensate for the reduced protein content under elevated CO2. Yet the opposite is expected under associated temperature increases (see Section 5.4.1.2).

Large areas of upland Britain are already colonised by relatively unpalatable plant species such as bracken, matt grass and tor grass. At elevated CO2 further changes may be expected in the dominance of these species, which could have detrimental effects on the nutritional value of extensive grasslands to grazing animals (Defra, 2000).

New Knowledge: Thermal stress reduces productivity, conception rates and is potentially life-threatening to livestock.

The TAR indicated the negative role of heat stress for productivity. Because ingestion of food and feed is directly related to heat production, any decline in feed intake and/or energy density of the diet will reduce the amount of heat that needs to be dissipated by the animal. Mader and Davis (2004) confirm that the onset of a thermal challenge often results in declines in physical activity with associated declines in eating and grazing (for ruminants and other herbivores) activity. New models of animal energetics and nutrition (Parsons et al., 2001) have shown that high temperatures put a ceiling on dairy milk yield irrespective of feed intake. In the tropics, this ceiling reaches between half and one-third of the potential of the modern (Friesians) cow breeds. The energy deficit of this genotype will exceed that normally associated with the start of lactation, and decrease cow fertility, fitness and longevity (King et al., 2005).

Increases in air temperature and/or humidity have the potential to affect conception rates of domestic animals not adapted to those conditions. This is particularly the case for cattle, in which the primary breeding season occurs in the spring and summer months. Amundson et al. (2005) reported declines in conception rates of cattle (Bos taurus) for temperatures above 23.4°C and at high thermal heat index.

Production-response models for growing confined swine and beef cattle, and milk-producing dairy cattle, based on predicted climate outputs from GCM scenarios, have been developed by Frank et al. (2001). Across the entire USA, the percentage decrease in confined swine, beef and dairy milk production for the 2050 scenario averaged 1.2%, 2.0% and 2.2%, respectively, using the CGC (version 1) model and 0.9%, 0.7% and 2.1%, respectively, using the HadCM2 model.

New Knowledge: Increased climate variability and droughts may lead to livestock loss.

The impact on animal productivity due to increased variability in weather patterns will likely be far greater than effects associated with the average change in climatic conditions. Lack of prior conditioning to weather events most often results in catastrophic losses in confined cattle feedlots (Hahn et al., 2001), with economic losses from reduced cattle performance exceeding those associated with cattle death losses by several-fold (Mader, 2003).

Many of the world's rangelands are affected by ENSO events. The TAR identified that these events are likely to intensify with climate change, with subsequent changes in vegetation and water availability (Gitay et al., 2001). In dry regions, there are risks that severe vegetation degeneration leads to positive feedbacks between soil degradation and reduced vegetation and rainfall, with corresponding loss of pastoral areas and farmlands (Zheng et al., 2002).

A number of studies in Africa (see Table 5.3) and in Mongolia (Batima, 2003) show a strong relationship between drought and animal death. Projected increased temperature, combined with reduced precipitation in some regions (e.g., Southern Africa) would lead to increased loss of domestic herbivores during extreme events in drought-prone areas. With increased heat stress in the future, water requirements for livestock will increase significantly compared with current conditions, so that overgrazing near watering points is likely to expand (Batima et al., 2005).

5.43.2 Impacts of gradual temperature change

A survey of experimental data worldwide suggested that a mild warming generally increases grassland productivity, with the strongest positive responses at high latitudes (Rustadetal.,2001). Productivity and plant species composition in rangelands are highly correlated with precipitation (Knapp and Smith, 2001) and recent findings from IPCC (2007b) (see Figure 5.1) show projected declines in rainfall in some major grassland and rangeland areas (e.g., South America, South and North Africa, western Asia, Australia and southern Europe). Elevated CO2 can reduce soil water depletion in different native and semi-native temperate and Mediterranean grassland (Morgan et al., 2004). However, increased variability in rainfall may create more severe soil moisture limitation and reduced productivity (Laporte et al., 2002; Fay et al., 2003; Luscher et al., 2005). Other impacts occur directly on livestock through the increase in the thermal heat load (see Section 5.4.3.1).

Table 5.3 summarises the impacts on grasslands for different temperature changes. Warming up to 2°C suggests positive impacts on pasture and livestock productivity in humid temperate regions. By contrast, negative impacts are predicted in arid and semiarid regions. It should be noted that there are very few impact studies for tropical grasslands and rangelands.

5.4.4 Industrial crops and biofuels

Industrial crops include oilseeds, gums and resins, sweeteners, beverages, fibres, and medicinal and aromatic plants. There is practically no literature on the impact of climate change on gums and resins, and medicinal and aromatic plants. Limited new knowledge of climate change impacts on other industrial crops and biofuels has been developed since the TAR. Van Duivenbooden et al. (2002) used statistical models to estimate that rainfall reduction associated with climate change could reduce groundnut production in Niger, a large groundnut producing and exporting country, by 11-25%. Varaprasad et al. (2003) also concluded that groundnut yields would decrease under future warmer climates, particularly in regions where present temperatures are near or above optimum despite increased CO2.

Impacts of climate change and elevated CO2 on perennial industrial crops will be greater than on annual crops, as both damages (temperature stresses, pest outbreaks, increased damage from climate extremes) and benefits (extension of latitudinal optimal growing ranges) may accumulate with time (Rajagopal et al., 2002). For example, the cyclones that struck several states of India in 1952,1955,1996 and 1998 destroyed so many coconut palms that it will take years before production can be restored to pre-cyclone levels (Dash et al., 2002).

The TAR established large increases in cotton yields due to increases in ambient CO2 concentration. Reddy et al. (2002), however, demonstrated that such increases in cotton yields were eliminated when changes in temperature and precipitation were also included in the simulations. Future climate change scenarios for the Mississippi Delta estimate a 9% mean loss in fibre yield. Literature still does not exist on the probable impacts of climate change on other fibre crops such as jute and kenaf.

Biofuel crops, increasingly an important source of energy, are being assessed for their critical role in adaptation to climatic change and mitigation of carbon emissions (discussed in IPCC, 2007c). Impacts of climate change on typical liquid biofuel crops such as maize and sorghum, and wood (solid biofuel) are discussed earlier in this chapter. Recent studies indicate that global warming may increase the yield potential of sugar beet, another important biofuel crop, in parts of Europe where drought is not a constraint (Jones et al., 2003; Richter et al., 2006). The annual variability of yields could, however, increase. Studies with other biofuel crops such as switchgrass (Panicum virgatum L.), a perennial warm season C4 crop, have shown yield increases with climate change similar to those of grain crops (Brown et al., 2000). Although there is no information on the impact of climate change on non-food, tropical biofuel crops such as Jatropha and Pongamia, it is likely that their response will be similar to other regional crops.

5.4.5 Key future impacts on forestry

Forests cover almost 4 billion ha or 30% of land; 3.4 billion m3 of wood were removed in 2004 from this area, 60% as industrial roundwood (FAO, 2005b). Intensively managed forest plantations comprised only 4% of the forest area in 2005, but their area is rapidly increasing (2.5 million ha annually (FAO, 2005b)). In 2000, these forests supplied about 35% of global roundwood;

Table 5.3. Impacts on grasslands of incremental temperature change. (EXP = experiment; SIM = simulation without explicit reference to a SRES scenario; GMT = global mean temperature.)

Local temperature change

Sub-sector

Region

Impact trends

Sign of impact

Scenario/Experiment

Source

+0-2°C

Pastures and livestock

Temperate

Alleviation of cold limitation increasing productivity Increased heat stress for livestock

+

0 0

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