Adapting livestock systems to climate change

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<ul><li><p>Adapting livestock systems to climate change in South Asia</p><p>M. Herrero, P. K. Thornton and I. WrightClimate change vulnerability and adaptation in the livestock sector28th-29th October 2010 | Kathmandu, Nepal</p><p>*</p></li><li><p>Background</p><p>Living with uncertainty</p><p>Climate change impacts</p><p>Adaptation options</p><p>ConclusionsOutline</p><p>*</p></li><li><p>Agriculture in South Asia is changing rapidly and there are large numbers of people to feed</p><p>Need to try to understand how production systems will change in the future: the target is moving!</p><p>for designing a more coherent and dynamic research and policy agenda that benefits the poor</p><p>for targeting investments more adequately</p><p>For reducing vulnerability and poverty Background</p><p>*</p></li><li><p>Lots of drivers of future changePopulation / Urbanization Growth in demand and its natureIncreased competition for natural resources Trade / exchange of knowledge and </p><p>productsClimate change warmer and more variable</p><p>**</p></li><li><p>Human populationUNEP 2007</p><p>*</p></li><li><p>Revised demand for livestock products to 2050Rosegrant et al 2009</p><p>Annual per capita consumptionTotal consumptionyearMeat (kg)Milk (kg)Meat (Mt)Milk (Mt)Developing2002205028444478137326222585Developed200220507894202216102126265295</p><p>*</p></li><li><p>Cereal yieldsIncreasing.except in Sub-Saharan AfricaWorld Bank 2007</p><p>*</p></li><li><p>Area under cultivation and rates of growth in cereal yieldsWorld Bank 2007</p><p>*</p></li><li><p>Mixed intensive systems in the developing World are under significant pressures (Herrero et al. 2010) 2.5 billion people3.4 by 2030, predominantly in Asia150 million cattle increasing to almost 200 million by 2030Most pigs and significant numbers of poultry, increasing by 30-40% to 2030Crop yields stagnating: wheat, riceOthers increasing: maize (East Asia)All in the same land!</p><p>Severe water constraints in some placesSoil fertility problems in others</p><p>*</p></li><li><p>...and then theres climate change... </p><p>*</p></li><li><p>Why is climate change so important to agriculture-based countries?de Jong (2005), World Bank (2005)Ethiopia: Rainfall Variability and Growth in Gross Domestic Product (GDP)</p><p>*</p></li><li><p>Climate change: we need to act even when there are still uncertainties...but the science is improving! </p><p>*</p></li><li><p>Climate change recognised long ago</p><p>Climate change science timelineCourtesy of R. Conant</p><p>*</p><p>*</p></li><li><p>But the policy frameworks have been slowly implemented </p><p>Climate policy timeline1992: Rio Treaty establishes UNFCCCA modest proposal?</p><p>Near-term implementation of a global policy that affects all parts of everyones lives.Courtesy of R. Conant</p><p>*</p><p>*</p></li><li><p>P.G. Jones CIAT Land Use Project March 2004</p><p>Temperature </p><p>Random series gently rising</p><p>*What this means to farmers is that they are likely to experience more events that stretch their capacity to cope</p></li><li><p>What are the impacts of climate change on livestock systems?</p><p>*</p></li><li><p>Increases in temperature</p><p>Increases in boreal winter and summer rainfall in places but more variable</p><p>More snow melt</p><p>Higher frequency of extreme events (rainfall and wind cyclones)</p><p>Disruption of monsoon patterns</p><p>Climate change impacts in South Asia (IPCC 2007)</p><p>*</p></li><li><p>Asia | Length of growing period | Current conditions</p></li><li><p>Asia | Changes in the length of growing period | 2000 2050 (Thornton et al 2008)</p></li><li><p>Percent change in annual runoff by 2041-60 relative to 1900-70, scenario A1B, usingan ensemble of 12 climate models (Milly et al., 2005, as in Fig 3.4 in AR4-WGII)</p><p>More runoff</p></li><li><p>Increases in precipitation may not translate into higher crop yields due to increased rainfall variability...and only if input supply is appropriate</p><p>*</p></li><li><p>A game of winners and losers</p><p>Simulated percentage maize production changes to 2030 and 2050, by country and systemMean of 4 combinations of GCM and emissions scenarioThornton et al. (2010)WinnersLosers</p><p>National ProductionMixed rainfed temperateMixed rainfed humidMixed rainfed arid20302050203020502030205020302050Burundi9.19.114.418.1-1.8-8.8-- Kenya15.017.833.346.5-4.6-9.8-1.1-8.4Rwanda10.814.913.418.85.43.61.12.7Tanzania-3.1-8.17.58.7-1.6-6.4-5.1-11.1Uganda-2.2-8.64.93.1-4.6-12.9-1.1-6.3</p><p>*</p></li><li><p>Mostly mediated via changes in land use and ecosystems</p><p>Not completely understood</p><p>Significant implications for:Land useFood securityProduction of feedsDistribution of diseases and/or their vectors (i.e. tryps)Water availabilityBiodiversityGreen house gas emissions (i.e methane)</p><p>Increased frequency of climatic extreme events (drought/floods)erosion, soil degradationClimate change impacts on livestock systems</p><p>*</p></li><li><p>Other key issues in scarce resource situations</p><p>Power structures</p><p>Governance</p><p>Equity / Gender issues</p><p>VulnerabilityClimate change impacts on livestock systems</p><p>*</p></li><li><p>Adaptation to climate change in livestock systems</p><p>*</p></li><li><p>Adaptation options will depend largely on the how we shape the worldSeveral options exist though largely dependent on our vision of world development and how it plays out in different regions</p><p>Lots of scenarios and uncertainty!</p><p>Different paradigms of agricultural development (industrial vs pro-poor smallholders, large vs family farms)Globalisation and trade patternsConsumption patternsCarbon constraintsRoles and incentives for technology adoptionGrowth in other sectorsPower relationships</p><p>*</p></li><li><p>Main types of optionsSustainable intensification </p><p>Extensification</p><p>Income diversification</p><p>Exit from agriculture</p><p>All require a mixture of management, technology / supporting policies and investments</p><p>No single path best, mixtures required in different parts of the world</p><p>*</p></li><li><p>Sustainable intensificationSome featuresAppropriate for some mid to high potential areasTechnology / management essentialImproved feeding systemsBetter breedsInputs (fertiliser / supplementation)</p><p>Market incentives / creationService and input provisionRegulations and standards</p><p>Investment in infrastructure (roads, post-harvest facilities, cooling plants, others)</p><p>Herrero et al 2010</p><p>*</p></li><li><p>Pros and consPotentially very easy and cheap to increase productivity, especially in smallholder systems with large yield gaps but market incentives are needed</p><p>Some adaptation practices can also lead to mitigation and vice-versai.e. Improved feeding : higher milk yields / lower GHG per unit of product</p><p>How do we define it and when does it become unsustainable? No guidelines or indicators widely applicable for a range of circumstances / systemsThough lots of progress in Europe</p><p>Herrero et al 2010</p><p>*</p></li><li><p>Diversification of livelihood strategies Common in many systems (Thapa et al.)</p><p>Diversification of income with farm or non-farm enterprises</p><p>Income and cash flow stability</p><p>Risk reduction</p><p>Reduced variability of food supply / income (mostly in arid areas)</p><p>**</p></li><li><p>Some examples of adaptation optionsBreed or species changes (crops and livestock)</p><p>Rangeland management</p><p>Development of water sources</p><p>Supplementation strategies</p><p>Disease control and surveillance</p><p>Policies, support tools and regulations (including insurance, early warning, etc)Payments for ecosystems services (water, biodiversity, etc)</p><p>Alternative activities: fish farming, more cropping, horticulture where possible, other livestock (chickens)</p><p>Off farm-income</p><p>*</p></li><li><p>*</p></li><li><p>*</p></li><li><p>In intensive systems, feed shortages for ruminants might increase demand for cereals further. If these end up being fed on grainsthis might lead to reduce food consumption of poor people furthergrainslivestockproductshumanconsumptionlivestockenergyMonogastrics mostly+ ruminantsFurther increases?</p><p>Chart1</p><p>31.793916893327.0097957214</p><p>28.665906395622.4250417591</p><p>16.966889170714.2075185357</p><p>24.957679005517.2578876174</p><p>11.54631861156.4935982018</p><p>-9.6136828842-12.5022279992</p><p>74.97514964353.5569317031</p><p>145.243951174797.4514409101</p><p>278.9143168632121.4631066271</p><p>289.4719595311164.6453740179</p><p>61.361491133758.9352155056</p><p>75.196528311652.7787505484</p><p>191.5545269044134.1749598912</p><p>151.643286897192.7097813252</p><p>120.281248212571.9101575207</p><p>126.905508410890.2567843907</p><p>220.1663723592152.4638520977</p><p>132.100003346761.8002054442</p><p>93.95779925668.3389093487</p><p>131.931974243591.0755420059</p><p>biofuels 2030</p><p>reference 2030</p><p>% change from 2000</p><p>Sheet1</p><p>World food prices ($/ton)</p><p>% change from 2000 prices</p><p>2000baseline 2030biofuels 2030irrigation expansion 2030low meat demand 2030baseline 2030biofuels 2030irrigation expansion 2030low meat demand 2030</p><p>beef191724352527191924612732028</p><p>pork9061109116585511242229-624</p><p>lamb270530893164207231101417-2315</p><p>poultry1196140314951649142717253819</p><p>eggs761810848591820612-228</p><p>milk302264273207266-13-10-31-12</p><p>rice18528432428129754755261</p><p>wheat10921626823623297145115112</p><p>maize91203347240231121279162152</p><p>ogrn68181266218207165289219203</p><p>soybeans20632733230131559614653</p><p>potatos21332537336334353757161</p><p>sweet potatos4721105137614101201134192199155</p><p>cassava6512516315213493152135107</p><p>meal1952923121372975060-2953</p><p>oils4817219193907305091-1952</p><p>vegetables43453061959259022423636</p><p>subf34451455154352450605852</p><p>temf35457565162361762847674</p><p>sugar cane271465596512494721208983</p><p>sugar beet26739041042641346545954</p><p>millet25548557859551290127134101</p><p>sorghum93234297290251152220213171</p><p>chickpea53486312381224111862132130110</p><p>pigeon pea47079091187682568948776</p><p>groundnut4318239997948709113284102</p><p>cotton1258139614821389142311181013</p><p>other220602777622638174254183191</p><p>swtn214202213180206-6-1-16-4</p><p>baseline 2030biofuels 2030irrigation expansion 2030low meat demand 2030</p><p>beef2732028</p><p>pork2229-624</p><p>lamb1417-2315</p><p>poultry17253819</p><p>eggs612-228</p><p>milk-13-10-31-12</p><p>rice54755261</p><p>wheat97145115112</p><p>maize121279162152</p><p>oil grains165289219203</p><p>soybeans59614653</p><p>potatos53757161</p><p>sweet potatos134192199155</p><p>cassava93152135107</p><p>sugar cane721208983</p><p>millet90127134101</p><p>sorghum152220213171</p><p>chickpea62132130110</p><p>pigeon pea68948776</p><p>groundnut9113284102</p><p>Sheet1</p><p>biofuels 2030</p><p>reference 2030</p><p>% change from 2000</p><p>Sheet2</p><p>Sheet3</p><p>*</p></li><li><p>Moving megajoules: fodder markets are likely to expand in areas of feed deficits as demand for milk and meat increasesIndia quotes from M Blummel</p><p>Stovers transported morethan 400 km to be sold</p><p>Price has doubled in 5 years, now 1/3 (2/3) of grain value of sorghum</p><p>Farmers paying for stoverqualityHerrero et al. in prep</p><p>*</p></li><li><p>ConclusionsClimate change is happening but we need to act even if the magnitude of the impacts is uncertain</p><p>Impacts of climate change on livestock and agriculture in South Asia heterogeneous but potentially severe</p><p>A game of winners and losers</p><p>Need significant investment in adaptation (infra-structure, markets will be essential)</p><p>Adaptation: No silver bullets, suites of alternatives</p><p>Good development is the best solution for dealing with climate change and variability </p><p>Large role for research (crops, livestock, systems, value chains, markets, innovation systems and others) </p><p>*</p></li><li><p>Thank you</p><p>*</p><p>*</p><p>*</p><p>*</p><p>**</p><p>*</p><p>*</p><p>*</p><p>*</p><p>*</p><p>*</p><p>*</p><p>*</p><p>*</p><p>**</p><p>**What this means to farmers is that they are likely to experience more events that stretch their capacity to cope*</p><p>*</p><p>*</p><p>*</p><p>*</p><p>*</p><p>*</p><p>*</p><p>*</p><p>*</p><p>*</p><p>**</p><p>*</p><p>*</p><p>*</p><p>*</p><p>*</p><p>*</p><p>*</p></li></ul>

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