Guide Crop Responses to Global Warming

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In a recent study published in the Journal of Experimental Botany , a team of scientists investigated the effects of temperature on photosynthesis, the process by which plants transform sunlight into grain and leaves. Every plant on the planet uses photosynthesis to capture carbon dioxide from the atmosphere, but not all plants do it in the same way. Plants like wheat and rice use the ancient, less efficient C 3 photosynthetic path, while other plants such as maize and sorghum use the more efficient C 4 path.

These plants are specially adapted to thrive in hot and dry environments, like the ones that are expected to be more prevalent in future decades. Credit: Western Sydney University. This necessitates that all economic activities are represented in the model. Financial flows as well as commodity flows within a country and at the international level are consistent in the sense that they balance. The country models are linked through trade, world market prices and financial flows. The system is solved in annual increments, simultaneously for all countries.

It is assumed that supply does not adjust instantaneously to new economic conditions. Only supply that will be marketed in the following year is affected by possible changes in the economic environment. A first round of exports from all the countries is calculated for an initial set of world prices, and international market clearance is checked for each commodity.

World prices are then revised, using an optimizing algorithm, and again transmitted to the national models. Next, these generate new domestic equilibria and adjust net exports. This process is repeated until the world markets are cleared in all commodities. At each stage of the iteration the domestic markets are in equilibrium. Since these steps are taken on a year-by-year basis, a recursive dynamic simulation results. An upper bound on land available for cropping and for use as pasture is determined by the availability of land resources as well as economic conditions; e.

The responsiveness of how much land can be cultivated due to changing economic conditions is rather low since time and investment are needed to bring new land into cultivation. Technological development is assumed to be largely determined by exogenous factors. Technical progress is included in the models as biological technical progress in the yield functions of both crops and livestock. Rates of technical progress were estimated from historical data and, in general, show a decline over time.

Mechanical technical progress is part of the function determining the level of harvested crop area and livestock husbandry. Induced endogenous technical progress is not considered for any of these cases or for non-agricultural production. Information generated by simulating with the BLS consists of a number of variables. At the world-market level these include prices, net exports, global production and consumption. At the country level, the information generated includes: producer and retail prices, level of production, use of primary production factors land, labour and capital , intermediate input use feed, fertilizer and other chemicals , level of human consumption, stocks and net trade, gross domestic product and investment by sector, population number and labour force, welfare measures such as equivalent income, and the level of policy measures as determined by the government e.

The standard reference scenario we describe, termed scenario REF-M, assumes 'business as usual' in the sense that no radical shifts in technological and political trends are included. Protectionist policy measures in agriculture, however, are assumed to be lowered to half the observed historical levels.

The transition to such reduced protection of the agriculture sectors is implemented between the beginning of the simulation period and year Thereafter the respective policy settings are kept constant. Another reference projection, scenario REF-H, assumes faster economic growth than the standard reference scenario. In the BLS, the dynamics of economic growth can be influenced by adjusting the rate of investment to the amount of technical progress. Similarly, a lower growth simulation run, scenario REF-L, has been created by curtailing investments in favour of consumption. Two projections deal with the sensitivity of the world food system with respect to land development and availability of agricultural inputs.

In addition, a ceiling on fertilizer use per hectare was enforced. Both these scenarios were simulated to test the impact of possible agricultural policies geared towards reducing greenhouse gas emissions from agriculture specifically, CO 2 release from deforestation and N 2 O emissions from nitrogen fertilizers. Finally, reference projection REF-MP uses the economic assumptions of the standard reference run REF-M but alters the demographic projections from medium population growth to low population growth.

All the simulations are carried out on a yearly basis from to Since the UN projected national population levels only up to the year , the remainder of the projection period was covered by growth rates compiled from long-term population projections of the World Bank Table 9.

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Labour participation rates are taken from projections of the International Labour Organization. The allocation of total labour force between agriculture and non-agricultural sectors responds to relative prices and incomes. During the last two decades, population at the global level has been growing at an average rate of about 1.

In the BLS standard reference projection, the average annual population growth rate is projected to decline gradually from 1. This would bring global population numbers to 6 million in year and about 10 million in year In , almost 9 million people are projected to live in developing countries, of which approximately 5 million are in Asia, and 2 million in Africa. ECONOMIC GROWTH Growth rates in most of the national models of the BLS are determined based on three elements: a capital accumulation through investment and depreciation, related to a savings function that depends on lagged GDP levels as well as balance of trade and financial aid flows, b dynamics of the labour force as a result of demographic changes, and c technical progress.

Estimated population and average annual growth, year Region mill. The declining rates of population growth and the related decline in the growth of the labour force as well as a general slowdown in productivity increases contribute to this development.

In the standard reference scenario, GDP at the global level increases at an average 2. Economic growth declines to about 1. Overall, global GDP increases 4. This results in an average annual increase in GDP per caput of 1. It should be noted, however, that increases in per caput indicators are higher at regional and national levels compared to global figures owing to an aggregation effect induced by the demographic development, giving increasingly higher weights to poorer developing countries.

Similarly, food production measured in terms of net food energy, i. Technological progress and economic development assumed in the reference scenario allow this increase in demand to be met at somewhat decreasing world market prices for agricultural products, consistent with historical trends. Global trade in the reference scenario increases somewhat faster than global agricultural production. In general, the share of global trade in global production of commodity aggregates increases gradually over time indicating a growing specialization in production.

To evaluate the impact of alternative scenarios on the poor in different countries, it was necessary to generate a consistent hunger indicator in the BLS. Country-wise estimates of the number of undernourished persons have been made by FAO , To recover the FAO method in a reduced form, suitable for use in the simulation models, a cross-country regression has been estimated explaining the share of people at risk of hunger by a measure of food energy availability relative to nutritional requirements. Food availability, in turn, depends on income and price levels.

Yet, despite this remarkable improvement the estimated number of people at risk of hunger increases somewhat, from about million 2 in to almost million in year , and some million in the year The projected number of undernourished people in developing countries is shown in Table 9. No estimate was attempted for developed regions.

Of course, the projected number of people at risk of hunger is sensitive to the scenario assumption, ranging from less than million under the low population run, about million assuming faster economic development, to about million under the lower growth scenario. These estimates are based on a threshold food energy level of 1. The BLS estimates assume a lower threshold of 1. While the estimates show an improvement of the food security situation both in relative and absolute terms in Asian countries, the African continent experiences a mixed outcome largely due to the dramatic population increase.

However, the number of hungry is projected to increase more than three-fold, from about million people in to million in , thereby making Africa the region with the largest number of undernourished. An assessment of the world food system under alternative scenarios The evaluation of the potential impact of climate change on production and trade of agricultural commodities, in particular on food staples, is carried out by comparing the results of the climate change scenarios to the reference projections.

Various aspects of these reference projections have been presented in the previous section. Well over 70 experiments have been simulated. Results from six sets of simulation experiments are reported here: 1. Simulations without physiological effects of ppm CO 2 on crop growth and yield. Simulations with physiological effects of ppm CO 2 on crop growth and yield.

Simulations with physiological effects of ppm CO 2 on crop growth and yield, and adaptations to mitigate negative yield impacts at the farm-level that would not involve any major changes in agricultural practices Adaptation Level 1. Simulations with the physiological effects of ppm CO 2 on crop growth and yield, and adaptations at the farm-level that, in addition to the former, would also involve major changes in agricultural practices Adaptation Level 2.

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Simulations with the physiological effects of ppm CO 2 on crop growth and yield, but with temperature and precipitation changes projected by the GISS GCM for the s. METHODS Data on crop yield changes estimated for the different scenarios of climate change were compiled for 34 countries or major regions of the world. Most models included in the BLS distinguish between yield and acreage functions. The yield response functions of major crops use the level of fertilizer application and a term related to technology as explanatory variables.

While technical progress is specified relative to a time trend, the level of fertilizer application is derived from optimality conditions, i. Yield variations caused by climate change were introduced into the yield response functions by means of a multiplicative factor applied to the relevant parameters in the mathematical representation.

This implies that both average and marginal fertilizer productivity are affected by the imposed yield changes. Alternative schemes for introducing yield changes are conceivable, e. More empirical knowledge with regard to the effect of climate-induced yield changes on marginal productivity is needed to select the most appropriate implementation. It should be noted, however, that the BLS is equipped to handle explicit area constraints in the resource allocation module of the agricultural production component.

The adjustment processes taking place in the different scenarios are the outcome of the imposed yield changes triggering changes in national production levels and costs, leading to changes of agricultural prices in the international national markets. This in turn affects investment allocation and labour migration between sectors as well as reallocation of resources within agriculture. Time is an important aspect in this assessment: the yield modifications due to climate change are assumed to start occurring in , reaching their full impact in year This allows the economic actors in the national and international food system to adjust their behaviour over a year period.

Yet, the dynamic impacts in some of the scenarios are sizeable. For the GISS transient scenario A, climate change yield impacts were phased in linearly between the climate 'snapshots', i. Beyond year the yield change multiplier is extrapolated extending the trend of the period This measure of distortion is termed the static climate change yield impact, as it measures the hypothetical effect of yield changes without adjustments of the economic system taking place over time.

It refers to a state of the system that is not in equilibrium. As such it is only of theoretical interest, but helps in the understanding and quantification of the nature and magnitude of adjustments taking place due to changing economic conditions. Such an assumption is not regarded as very probable and will not be further discussed in the analysis. When direct physiological effects of CO 2 on yields are included, the magnitude and even the direction of the aggregate static impact at the world level varies with GCM climate scenario and with the assumptions regarding farm-level adaptation.

Responses of crop yield growth to global temperature and socioeconomic changes

In all cases the most negative effects are obtained in scenarios using the UKMO climate change scenario, which has the highest mean global warming, 5. Results derived from the GISS scenario show only small negative effects or even gains at the global level. The impacts are, however, quite unevenly distributed. At the aggregate level, developed countries experience an increase in productivity in all but the UKMO scenario.

In contrast, developing regions suffer a loss in productivity in all estimates presented here. Impacts on developing regions are all negative, except for the group of Centrally Planned Asia that includes China. Note, however, that the global increase is estimated to be more than twice the gain in developing countries. In the scenario assumptions, however, yield productivity changes are introduced gradually to reach their full impact only after a year period, from to In scenarios with shortfalls in food production caused by climate change, market imbalances push international prices upwards and provide incentives for reallocation of capital and human resources.

At the same time, consumers react to price changes and adjust their patterns of consumption.

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Effect of CO 2 When direct physiological effects of CO 2 on plant growth and yields are not included, major increases in world market prices result in four- to nine-fold increases of cereal prices depending on GCM scenario. Apart from the scientific evidence of the beneficial physiological effects of elevated CO 2 levels on crop yields, such increases would elicit strong public reaction and policy measures to mitigate the negative yield impacts.

Hence, the outcome for scenarios without the physiological effects of CO 2 on yields are probably unrealistically extreme. On the other hand, under the GISS-A climate scenario, where impacts are dominated by positive physiological effects of CO 2 , major price decreases occur. Price changes are further reduced when farm-level adaptation is considered. The UKMO projection, however, still produces a two-thirds crop price increase.

  • 9. The potential effects of climate change on world food production and security.
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Then, as negative impacts in developing countries increase and beneficial impacts in developed countries level off, prices return to and finally exceed the price index of the reference scenario. With adaptation measures involving major changes in agricultural practices, i. Note that the assumptions underlying Adaptation Level 2, sometimes requiring major investments, may not be economically viable. Scenarios with low-cost adaptation measures, i. Developed countries are likely to experience some increase in agricultural output. On the contrary, developing countries are projected to suffer a production loss in most scenarios.

Dynamic impacts in developing regions are mostly negative except for Centrally Planned Asia which benefits in all these scenarios.

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Impact of climate change on crop prices direct CO 2 effects and farm-level adaptation taken into account It is important to note that these changes in comparative advantage between developed and developing regions are likely to accentuate the magnitude of the static impacts suggested by the analysis without economic adjustment. Winners are likely to gain more, and losers to lose even more. We can distinguish two prototypical situations in these scenario results. Then the shift in relative productivity from developing to developed regions dominates the adjustment process.

For instance, in the GISS and GFDL scenarios with farm-level adaptation, agriculture production shifts somewhat from developing to developed countries taking account of the differences in projected yield changes. These in turn provide production incentives to both regions to recover more than half the production forgone due to climate change according to static crop model estimates. This is likely due to the location of major wheat-producing regions at mid and high latitudes, where yield declines are projected to be lower.

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Net imports of cereals into developing countries increase under all scenarios. The change in cereal imports, relative to the standard reference projection, is largely determined by the magnitude of the estimated yield change, the change in relative productivity in developing and developed regions, the change in world market prices, and changes in real incomes of consumers in developing countries. For example, under the GISS climate change scenarios, productivity is altered in favour of developed countries with relatively small changes in incomes and prices, resulting in pronounced increases of net cereal imports into developing countries.

With less agricultural production in developing countries and higher prices on international markets, the estimated number of people at risk of hunger is likely to increase. This occurs in all but one scenario Table 9. Conclusions The distortions of the world food system simulated in the climate change scenarios fall well within the range of estimates obtained from the different reference projections. For instance, the decline in cereal production even under the worst climate change scenario based on the UKMO GCM experiment assuming physiological effects of increased atmospheric CO 2 concentrations and some farm-level adaptation , amounts to less than half the difference between the cereal production levels simulated in the higher and lower economic growth reference projections, scenarios REF-H and REF-L.

However, the ability of the world food system to absorb negative yield Table 9. Impact of climate change on regional cereal production, year , with physiological effects of ppm CO 2 and farm-level Adaptation 1 Figure 9. Impact of climate change on regional crop production, year , with physiological effects of ppm CO 2 and farm-level Adaptation 1 Figure 9. Impact of climate change on cereal commodities, year , with physiological effects of ppm CO 2 and farm-level Adjustment 1 impacts decreases with the magnitude of the impact.

The effects of changes in climate on crop yields are likely to vary greatly from region to region across the globe. The results of the scenarios tested in this study indicate that the effects on crop yields in mid- and high-latitude regions appear to be positive or less adverse than those in low-latitude regions, provided the potentially beneficial direct physiological effects of CO 2 on crop growth can be fully realized. From a development perspective, the most serious concern relates to the apparent difference in incremental yield impacts between developed and developing countries.

The scenario results suggest that if climatic change were to retard economic development beyond the direct effects on agriculture in the poorer regions, especially in Africa, then overall impacts could be sizeable. In all climate change scenarios, relative productivity of agriculture changes in favour of developed countries, with implications on resource allocation.


Economic feedback mechanisms are likely to emphasize and accentuate the uneven distribution of climate change impacts across the world, resulting in net gains for developed countries in all but the UKMO scenarios and a noticeable loss to developing countries. Impacts are assessed to be positive in almost all of the 10 aggregate world regions reported in the study.

However, the simulated percentage increases in developed countries are about twice the increases in developing regions. The analysis also shows that the yield impacts do not only vary with geographic region, but are also unequally distributed over time. Results of scenarios based on the GISS transient scenario A demonstrate that benefits from physiological effects due to increasing atmospheric CO 2 levels may outweigh negative impacts from changing temperature and precipitation regimes at least in the near-term.

The yield-increasing factors in that scenario dominate possible negative impacts until year Understanding the biophysical processes of CO 2 and climate change effects on crops remains an important research area. It must be realized, however, that the ability to estimate climate change yield impacts on world food supply, demand and trade is surrounded by large uncertainties regarding important elements, such as the magnitude and spatial characteristics of climate change, the range and efficiency of adaptation possibilities, the long-term aspects of technological change and agricultural productivity, and even future demographic trends.

Also, the adoption of efficient adaptation techniques is far from certain. In developing countries there may be social, economic or technical constraints, and adaptive measures may not necessarily result in sustainable production over long time-frames. Determining how countries, particularly developing countries, can and will respond to reduced yields and increased costs of food is a critical research need arising from this study. Will such countries be able to import large amounts of food?

Will the burden for adaptation be passed on to the poorest? From a political and social standpoint, the results of the study indicate the potential for a decrease in food security in developing countries. The study suggests that the worst situation arises from a scenario of severe climate change, low economic growth, continuing large population increases, and little farm-level adaptation. In order to minimize possible adverse consequences, like production losses, food price increases, environmental stresses, and an increase in the number of people at risk of hunger, the way forward is to encourage the agricultural sector to continue to develop crop breeding and management programmes for heat and drought conditions, in combination with measures taken to preserve the environment, to use resources more efficiently, and to slow the growth of the human population of the world.

The latter step would also be consistent with efforts to slow emissions of greenhouse gases, and thus the rate and eventual magnitude of global climate change. In the face of these uncertainties, both national and international organizations should encourage the development of new approaches likely to be effective in preparing for climate change. Agricultural research would benefit from increased attention to both macroclimate and microclimate in all experiments and variety trials.

Another climate change impact potentially significant for future agricultural production is soil organic matter loss due to soil warming. Considering the vulnerability of agricultural production to the occurrence of climate extremes, research should be directed to determine what are the heat-tolerance limits of currently grown and of alternative crops and varieties. At what threshold values of air or soil temperature do severe problems begin? What agronomic methods are the best to moderate the thermal regime affecting crop growth?

To the extent that the progressive greenhouse effect cannot be prevented in practice, policies should be devised to facilitate the adjustment of agriculture to the likelihood of environmental change. Such adjustments may include modification of agronomic practices, adoption of crops known to be heat-resistant and drought-resistant, increased efficiency of irrigation and water conservation, and improved pest management.

Such adjustments are worthy of being implemented in any case, be it with or without climatic change. Although some countries in the temperate zone may reap some benefits from climate change, many countries in the tropical and subtropical zones appear to be more vulnerable. Particular hazards are the possibly increased flooding of low-lying areas, the increased frequency and severity of droughts in semi-arid areas, and potential decreases in attainable crop yields. It happens that the latter countries tend to be the poorest and the least able to make the necessary economic adjustments.

Much of the expected change in global climate is due to the past and present activities of the industrial countries; so it is their responsibility to commit themselves to, and to play an active role in, a comprehensive international effort to prepare for the likely consequences.

References Adams, R. Global climate change in US agriculture. Nature : Adams, R. A reassessment of the economic effects of global climate change on U. Climatic Change 30 2 : Allen, L. Response of vegetation to rising carbon dioxide: photosynthesis, biomass and seed yield of soybean.

Global Biogrochemical Cycles 1 : Cure, J. Crop responses to carbon dioxide: A literature survey. Agricultural and Forest Meteorology 38 : Fourth World Food Survey. Fifth World Food Survey. World Agriculture Toward Agriculture: Towards FAO, Rome. Fischer, G.

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Kluwer Academic Publishers, Dordrecht. Hunger - Beyond the Reach of the Invisible Hand. Climate change and world food supply, demand and trade. Who benefits, who loses? Global Environmental Change 4 1 :