Global climate change models make projections about future climates based on current understanding of what drives climate change. These are then related to the potential impacts on crops, particularly cereal crops given the importance of global food security.Controlled field experiments grow crops in controlled environments where variables can be varied, for example the concentration of different gases in the atmosphere; the availability of water; and temperature levels. This is crucial in understanding how climate change affects individual crops. However, incorporating the results into large-scale climate change models remains wrought with uncertainty.Integrated climate-crop models attempt to address some of these problems, including the fact that individual crops react differently to outside drivers. But other factors, like changes in land use for example, may independently affect local climates, making it difficult for such models to be all-encompassing.Statistical analysis of past climates is used to determine the impact on past crop production and to estimate how such crops may respond in future. But this assumes that adequate historical data is available which is not always the case, nor is it certain that past reactions will be repeated.Climate change scenarios have been developed by the Intergovernmental Panel on Climate Change (IPCC - www.ipcc.ch), based on four different storylines of different future worlds. These differ in terms of projections in population growth, world GDP changes, differences in per capita income between developed and developing countries, and the energy level of the economy (related to emission levels).The common thread running through all these is complexity mixed with uncertainty. Thus, models have to simplify certain parameters, some of which may have large implications on their outcome. Generally, uncertainties become larger the further into the future projections are made. Furthermore, there is a substantial scale-gap between large-scale global climate models (which generally have a resolution of over 100km) and the small-scale of most farming systems (generally less than 10 km). Current climate modelling studies also have significant regional biases, due to a lack of data in many developing countries, for example on precipitation patterns. Also, different crops are believed to react differently to CO2 concentrations in the atmosphere. And finally there are events such as floods and droughts that are expected to become more frequent and more severe as a result of climate change. But predicting their impact is currently very difficult… Most modelling studies related to agricultural crops include projections of:
But, there are other relevant aspects and potential impacts that are hard to include in current models…Relationships between climate change and soil degradation. According to IPCC land management practices will be the most influential factor on the organic matter content of the soil during the next decades. Climate change is likely to increase the frequency and distribution of stronger winds and increased rainfall, both major determinants of erosion, likely leading to reduced soil capacity to hold water. This is of particular importance to crop production in semi-arid and arid areas, particularly if coupled with rising temperatures.Water availability: In a warmer world, the hydrological cycle is expected to become more intense, likely to result in 'very wet' and 'very dry' areas compared to past measurements. Globally, the number of people exposed to extreme droughts at any one time is also expected to increase as a result of climate change.Extreme events: These can influence agriculture quite heavily but projecting their impact is hard. Probably the best known such event is the El Niño Phenomenon that happens irregularly but dramatically affects the weather in many parts of the world. The term El Niño refers to the large-scale warming of surface waters of the Pacific Ocean every 3-6 years, which usually lasts for 9-12 months, but may continue for up to 18 months and dramatically affect the weather worldwide. Predicting the occurrence of El Niño events (but not their impact on agriculture) has only been possible since the 1980's when computing power became large enough to do so.The impact of El Niño on coffee production has been closely studied in Colombia. During its occurrence in the Andean region of Colombia, rainfall decreases while sun intensity and temperatures increase. This causes production to fall in some regions, particularly in low-lying areas where rainfall is less than 1,500 mm/year and there is low retention of moisture and high exposure of the crop to sunlight. Lack of water during the critical stages of fruit development also brings about a high risk of black beans, small beans and other defects, as well as increased incidence of pests such as coffee berry borer.