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The work must be attributed, but not in any way that suggests endorsement by ILRI or the author(s). NOTICE: For any reuse or distribution, the licence terms of this work must be made clear to others. Any of the above conditions can be waived if permission is obtained from the copyright holder. Nothing in this licence impairs or restricts the author’s moral rights. Fair dealing and other rights are in no way affected by the above. The parts used must not misrepresent the meaning of the publication. ILRI would appreciate being sent a copy of any materials in which text, photos etc. have been used. ISBN-13: 978 1 78924 185 3 (hardback) ILRI ISBN: 92-9146-586-3 (hardback) CABI Commissioning editor: Alexandra Lainsbury CABI Editorial assistant: Lauren Davies CABI Production editor: James Bishop Typeset by SPi, Pondicherry, India Printed and bound in the UK by Bell and Bain Ltd, Glasgow 16 Ruminant Livestock and Climate Change in the Tropics Polly Ericksen1, Philip K. Thornton2 and Gerald C. Nelson3 1International Livestock Research Institute, Nairobi, Kenya; 2CGIAR Research Programme on Climate Change, Agriculture and Food Security (CCAFS) and International Livestock Research Institute, Nairobi, Kenya, University of Edinburgh, UK; 3University of Illinois, Urbana-Champaign, Illinois, USA Contents Executive Summary 602 The problem 602 ILRI research 602 Research spending and bibliometrics 603 Scientific impact 603 Models 603 Data sets 603 Scientific results 603 Development impact 603 Capacity development and partnerships 604 The future 604 Livestock productivity 604 Mitigation and supply- and demand-side efforts 604 Introduction 604 Livestock Production Systems and Resource Use 605 Land 606 Water quantity 607 Water quality 607 Air 607 Ecosystem services 607 Climate Change Impacts on Ruminant Livestock 608 CGIAR research on climate change impacts in livestock systems 610 Weather data in climate analyses 610 Impacts on livestock systems 611 Current knowledge gaps on impacts 613 Adaptation of Livestock Systems to Climate Change 617 Costs of adaptation 617 CGIAR research on climate change adaptation in livestock systems 617 © International Livestock Research Institute 2020. The Impact of the International Livestock Research Institute (eds J. McIntire and D. Grace) 601 602 P. Ericksen, P. Thornton and G. Nelson Knowledge gaps on adaptation 618 Adaptation in mixed crop–livestock systems 619 Adaptation in pastoral systems 619 Mitigation of Greenhouse Gas Emissions from Livestock 620 Estimates of emissions from livestock 620 Mitigation via supply- and demand-side options 620 Supply-side options 621 Mitigation research in livestock systems 623 Demand-side options 628 The Future 630 References 631 Executive Summary therefore GHG emissions but mechanisms to gen- erate widespread change are not clear. The problem Adaptation to climate change will become more challenging with growing GHG concentra- The temperature and humidity changes associ- tions. At some point in this century, and in some ated with climate change will have direct and regions, temperature and humidity increases will for the most part adverse effects on tropical ani- make production biologically impossible. Well mal productivity. Related changes in pasture before that point, the adaptation costs are likely and feed productivity will have further indirect to outweigh economic benefits of producing live- adverse effects on productivity. Collectively, stock in many current producing regions. these effects will become increasingly negative as climate change progresses, reducing in- comes to both specialized and mixed livestock ILRI research producers and possibly reducing the incomes of consumers. The work of the International Livestock Research At the same time, livestock production ac- Institute (ILRI) on livestock and climate change tivities contribute to climate change. In the early began with studies of livestock water use 2000s, livestock production accounted for 18% (King, 1983; Sandford, 1983), agroecology, and of global greenhouse gas (GHG) emissions, with drought (Henricksen and Durkin, 1986) before enteric emissions about 25% of the total, emis- evolving into crop growing period models. sions from manure a further 24% and conver- Deeper global research efforts were stimulated sion of forests to pasture another 34%. Livestock by the publication of Livestock’s Long Shadow: En- also have negative environmental effects on vironmental Issues and Options by Steinfeld et al. water availability and quality, biodiversity and (2006), which was the first book to comprehen- other ecosystem services. sively address the environmental costs of live- A recent study showed per capita consump- stock. Steinfeld et  al. (2006) found that, while tion of animal products is likely to increase by livestock contributed significant shares of na- about 50% for low-income countries and about tional income, employment and protein supply, 10% for higher-income countries between 2010 it also had adverse effects on water and air qual- and 2050. This demand growth implies rising ity, contributed to deforestation and to loss of livestock GHG emissions unless cost-effective other ecosystem services, and generated 18% of mitigation options can be found. Options to re- anthropogenic GHG emissions. duce emissions include both supply and de- A second major impetus for ILRI research mand-side changes. On the supply side, technical was the Fifth Assessment Report (AR5) of the mitigation options can reduce emissions per unit Intergovernmental Panel on Climate Change of output substantially, but their economic feasi- (IPCC), published in 2014 (IPCC, 2014). AR5 bility varies by location and is generally under- was the first IPCC assessment to evaluate studied. On the demand side, changes in dietary climate change and livestock interactions. ILRI patterns can reduce meat consumption and researchers played important roles in this Ruminant Livestock and Climate Change in the Tropics 603 evaluation and extended their contributions in literature. Scientists in these activities have pub- subsequent work. lished extensively in prestigious scientific jour- This chapter provides an overview of both nals and their papers are widely cited. the scientific and the development impacts of ILRI research on climate change. Scientific Models i mpact is measured by advances in research methods and in research output, such as publi- MarkSim is a stochastic weather generator de- cations that advance our understanding of cli- veloped at Centro Internacional de Agricultura mate change and options to manage it. Tropical (Jones and Thornton, 2000) in the Development impact is about making a direct 1990s with ILRI input. It is used to downscale and positive contribution to welfare, directly or climate outputs from global climate models tem- indirectly. In the case of climate change, devel- porally to daily weather data and spatially from opment impact activities would include adop- large grid sizes of 2° latitude/longitude or more tion of adaptation and mitigation methods. down to a few kilometres. Scientific impact is relatively straightforward to The RUMINANT model, initially developed measure with bibliometric approaches. Measur- in the mid-1990s, was used to predict feed in- ing development impact is much more challen- take, nutrient supply and methane (CH 4) emis- ging because it often develops through long sions. These numbers are then aggregated to chains of causality; for example, an adviser to a systems, countries, regions and continents policy maker in a country reads a key academic using animal population projections, allowing reference that draws on a data set on coun- refinement of GHG emissions estimates related try-specific livestock systems that was generated to animal production. using a simulation model. Hence, assessments of development impact tend to be somewhat an- Data sets ecdotal in the absence of studies of adoption of new methods generated by research. Data sets produced by MarkSim and RUMINANT have been used by a wide range of researchers as well as by the model developers themselves. Research spending and bibliometrics Scientific results It was not possible to separate ILRI spending on Scientific results include the following: climate change from other spending in detail, but • Initial and periodic revisions of estimates of we do know that the climate research is the prod- area, production, livestock numbers and uct of a small number of scientists and hence the feed sources by systems in the tropics. budget share would be small in relation to the • Impacts of climate change on livestock prod- total. The productivity of climate change research, uctivity and production from changing tem- as shown in the Altmetric (www.altmetric.com/; perature and humidity, growing period accessed 7 March 2020) and bibliometric ana- shifts, and pest and disease distributions. lyses, is quite high and suggests that the field is • Identification of adaptation options. seriously underfunded when considering the im- • Estimates of GHG per animal and per system. portance of the problem, the scale of other inter- • Estimates of mitigation possibilities (e.g. national efforts and the productivity to date of percentage changes below the trend of ILRI research in this area. different climate scenarios). • Feed quality and its GHG impact in the tropics. Scientific impact Development impact The key scientific impacts of ILRI research on climate change arose from the development of The two main development impacts have been: (i) two models – MarkSim and RUMINANT – and appropriate animal selection, breeding and man- the use of these models to generate a range of agement techniques to reduce GHG per unit of data sets that are now widely used in the scientific output in the OECD countries; and (ii) modelling 604 P. Ericksen, P. Thornton and G. Nelson of supply and demand management options, Livestock productivity even if not yet broadly applied, which may have policy effects on GHG mitigation and ultimately The following questions need to be addressed: on global warming. • What are the productivity impacts in trop- ical livestock given temperature and hu- midity levels in producing regions under a Capacity development and partnerships range of climate scenarios? • How will climate change effects on livestock The principal capacity development impact of pests and diseases spill over into effects on the modelling work originating at ILRI has been livestock productivity? a wide range of partners who now use the • What types of livestock systems are most models, or the data sets generated from them. resilient to changes in both mean changes Some of these partners have been involved in and variability of temperature and humid- model development, validation and application; ity? One system in particular, confined ani- others have been trained to use the models for mal feeding operations (CAFOs), is likely to their own research needs. The creation of a web- grow rapidly in the tropics. How vulnerable site that generates MarkSim results for any arbi- are CAFOs to climate change? trary location extends the reach of the models • How cost-effective are existing adaptation dramatically. options? The second has been the development of • What are the biological limits to adapta- data and models under tropical conditions and tion? Are they likely to be reached in im- their applications. An example is the Mazingira portant producing areas? Centre at ILRI, which develops the capacity of • What are the potential effects of climate national and regional scientists to study inter- change on the use of livestock as a risk- actions between livestock and climate. management asset? • Will climate change alleviate or exacerbate livestock’s negative effects on water quality and quantity and on ecosystem services? The future Mitigation and supply- and The future for ruminant livestock is more cer- demand-side efforts tain on the demand side because of expected ris- ing incomes in developing countries and the Outstanding questions in this area include the high income elasticity of demand for animal following: products. It is projected that demand for all ani- • Are there technical and cost-effective op- mal products will grow globally, although there tions for reducing GHG emissions from will be composition effects as demand shifts existing livestock systems? among animal types and as competition from • What kind of changes to existing systems plant sources of protein grows. would achieve cost-effective mitigation? The future on the supply side is uncertain in • What policy activities could contribute to part because of the interactions between climate adoption of mitigation technologies? change and animal agriculture. Information on • What demand-side actions would be needed mitigation of, and adaptation to, climate change to have a substantial reduction in emissions is inadequate in the tropics compared with what and in what regions of the world? is known about the temperate zone. The re- search agenda stated here will require more de- tailed information on existing systems, on the Introduction potential for technical changes that contribute to adaptation and mitigation, on modelling such This chapter explores our understanding of the changes as new GCM outputs become available, evolving interactions between climate change and on policy changes that have the potential for and ruminant livestock in the tropics. It analyses significant adaptation and mitigation. the research done by ILRI and its partners in Ruminant Livestock and Climate Change in the Tropics 605 improving this understanding and in contribut- opportunities. The research undertaken by ILRI ing to solutions for mitigation of GHG emissions after Livestock’s Long Shadow became a major and adaptation to climate change. The focus is source of research outputs used in AR5. ILRI re- mostly on ruminants and, within this category, searchers were invited to participate in the IPCC on cattle. The chapter first reviews the scientific GHG emissions taskforce in 2009 on improving and development impacts of ILRI and partner GHG livestock emissions estimates. This work led research before suggesting research priorities on to collaboration with the International Institute climate change and tropical animal production. for Applied Systems Analysis (IIASA) and its ILRI’s predecessors did little on the global GLOBIOM model, a multi-market model with 30 environmental costs of tropical animal produc- regions covering the globe and coverage of some tion. ILRI’s research on livestock–climate change 18 or 27 commodities. This collaboration al- interactions began with the growing period mod- lowed a better disaggregation of livestock num- elling of Jones and Thornton (2000, 2003) and bers and feed sources by system, especially in the the studies of McDermott et al. (2001), Jones et al. tropics. A similar arrangement exists with the (2002) and Thornton et  al. (2002). Climate IMPACT multi-market model of IFPRI, with 158 change research at ILRI was stimulated by the regions and 60 commodities. publication of the Food and Agriculture Organiza- After a brief overview of livestock systems tion of the United Nations (FAO) book Livestock’s and their resource use, this chapter addresses Long Shadow: Environmental Issues and Options three areas: (i) climate change impacts on ru- (Steinfeld et al., 2006), which sought to ‘…assess minant livestock; (ii) adaptation of livestock sys- the full impact of the livestock sector on environ- tems to climate change; and (iii) options to mental problems, along with potential technical reduce GHG emissions. and policy approaches to mitigation’. Steinfeld et al. (2006) found that in the first decade of this century, livestock (including cattle, poultry and Livestock Production Systems pigs) contributed 40% of agricultural gross do- and Resource Use mestic product, employed 1.3 billion people and provided one-third of humanity’s protein intake. Following Seré and Steinfeld (1996) and Kruska However, livestock production also had major et al. (2003), Robinson et al. (2011) updated the negative environmental effects – polluting water most common classification for tropical livestock and altering water flows, contributing to biodiver- production. Level 1 in this classification de- sity loss and increasing air pollution as GHGs and scribed livestock production systems using land other noxious gases. Steinfeld et al. (2006, p. 112) characteristics. Level 2 linked potential to actual estimated that, in the early 2000s, livestock pro- livestock production and accounted for other en- duction accounted for some 18% of global GHG terprise options by referring to specific combin- emissions and for more than 80% of agricultural ations of crops and livestock. Level 3 addressed emissions. Extensive livestock systems contributed the intensity and scale of production by incorp- about 13% of global GHGs and intensive systems orating management practices. The resulting contributed about 5%. The major livestock sources classification has nine land-based systems and were enteric emissions (25% of the total), conver- two landless systems. The land-based systems sion of forests to pasture (34%) and manure have three climate categories – arid, humid and (about 24%) (Steinfeld et al., 2006, p. 113, Table temperate – and three agrosystem categories – 3.12). More recent estimates have revised these pastoral, mixed rainfed and mixed irrigated. The shares downwards, but livestock still is a major notation is LGA (livestock/grazing/arid), LGH contributor to global GHG emissions. (livestock/grazing/humid) and LGT (livestock/ A second impetus for new research on trop- grazing/temperate and topical); MRA (mixed/ ical livestock was the IPCC’s Fifth Assessment rainfed/arid and semi-arid), MRH (mixed/ Report (AR5; IPCC, 2014). AR5 was the first rainfed/humid) and MRT (mixed/rain-fed/tem- IPCC assessment to evaluate climate change and perate and tropical); and MIA (mixed/irrigated/ livestock interactions in some detail. It assessed arid), MIH (mixed/irrigated/humid) and MIT the literature on livestock adaptation to climate (mixed/irrigated/temperate and tropical). Map 2 change in addition to mitigation challenges and (p. xviii) shows the nine systems in Africa. 606 P. Ericksen, P. Thornton and G. Nelson Table 16.1. Livestock farming system extent and cattle numbers in Africa and Latin America, 2000. (Adapted from Robinson et al., 2011.) Area in Population in Cattle in Farming system Regiona 2000 (million km2) 2000 (million) 2000 (million TLUs) Agropastoral Central and South America 5.4 40.5 64.2 and pastoral East Asia 5.5 41.3 12.7 South Africa 0.5 19.2 6.2 South-east Asia 0.2 2.2 1.7 Sub-Saharan Africa 13.4 80.2 36.7 West Asia and North Africa 10.2 111.7 8.5 Total 35.2 295.1 129.9 Mixed extensive Central and South America 3.5 100.7 67.2 East Asia 1.7 195.4 20.3 South Africa 1.6 371.9 72.0 South-east Asia 1.2 85.3 10.2 Sub-Saharan Africa 5.1 258.7 55.5 West Asia and North Africa 0.9 87.2 5.3 Total 14.0 1099.2 230.6 Mixed intensifying Central and South America 2.4 221.2 69.4 potential East Asia 2.3 938.5 34.4 South Africa 1.8 844.6 109.5 South-east Asia 1.1 347.2 13.8 Sub-Saharan Africa 1.5 168.2 11.7 West Asia and North Africa 0.6 154.4 6.0 Total 7.3 2674.1 244.9 Other Central and South America 8.8 125.8 41.8 East Asia 1.5 104.2 9.8 South Africa 0.4 69.5 8.7 South-east Asia 1.9 40.4 7.1 Sub-Saharan Africa 4.1 109.2 6.8 West Asia and North Africa 0.2 31.3 1.4 Total 16.9 480.4 75.5 TLU, tropical livestock unit. aRegional groupings of countries are as listed in Thornton et al. (2002). Land C entral and South America and in South Asia, which would therefore have the greatest need for Table 16.1 provides statistics from Robinson et al. adaptation to climate change. (2011) for the areas of cattle-based livestock sys- An updated data set on ruminant meat and tems, estimates of the numbers of animals, and milk production by region and within region by human population by regions of Africa and Latin systems is shown in Fig. 16.5. America in 2000. The report provides similar CAFOs are part of the Seré and Steinfeld tables for pig and chicken systems in Asia. (1996) system and have been an important source Agropastoral and pastoral systems have by of production of cattle, poultry and swine in higher- far the greatest area with 35.2 million km2, of income countries for many years. FAO estimates which sub-Saharan Africa and West Asia and that 80% of growth in the livestock sector now North Africa are dominant. Mixed crop–livestock comes from these industrial production systems, systems occupy 23.8 million km2, of which sub- and this growth is likely to continue. CAFOs are Saharan Africa and Central and South America increasingly important in lower-income countries, dominate. Human and cattle population density especially for poultry, which now accounts are greatest in ‘mixed intensive’ systems in for 23 billion of the 30 billion farm a nimals, Ruminant Livestock and Climate Change in the Tropics 607 but lack of data makes it impossible to map them detail in the section below on mitigation. CAFOs, accurately outside the USA and Europe. ILRI has especially those that utilize feed concentrates done little research on CAFOs but these should be based on maize and soybean meal, generate nox- a topic for future work related to climate. ious odours that affect the quality of life in the immediate area and can be hazardous to human health. In addition, the manure generated can Water quantity be a large source of the GHGs nitrous oxide (N 2O) and CH4. One estimate is that livestock production ac- counts for almost 30% of water use in agricul- ture, most of which is water in crop production Ecosystem services for feed (Mekonnen and Hoekstra, 2010). Some research has contested this concept of Ecosystem services affected by livestock are of water use. Peden et  al., (2007) contend that two main types: (i) services provided by forests the majority of feed and fodder is rainfed, not that are lost as forested areas are converted irrigated; they propose an alternative notion, to pasture or crop production for feed; and that of livestock water productivity ‘defined as (ii) changes in grasslands that reduce a range the ratio of livestock’s beneficial outputs and of services, from water quality and quantity services to water depleted in their production’ availability to biodiversity. Quantifying defor- (Haileselassie et al., 2009). Haileselassie et al., estation is difficult because few countries col- (2009) found that livestock and water crop lect the needed data but de Sy et  al. (2015) productivity were comparable in rainfed sys- estimated that, of deforestation identified in the tems of Ethiopia. 2010 FAO Forest Resource Assessment, pasture was the dominant driver of forest area change (71.2%) and related carbon loss (71.6%) in Water quality South America, followed by commercial cropland (14% and 12.1%, respectively). Livestock reduce water quality principally by Changes in grassland ecosystem services manure runoff. Manure runoff increases both are driven by managed changes in species mix to faecal contamination of water, a major disease improve nutrient quality (see Chapter 11, this transmission mechanism where water treat- volume). Driscoll et  al. (2014) used data from ment is inadequate, and nutrient loads, which eight countries on six continents to show that have adverse human health effects and indirect few governments regulate conventionally bred effects on concentrations of harmful organisms pasture grasses to limit threats to these natural (e.g. algae blooms). Pesticides such as sheep- areas, even though these are bred with charac- dipping chemicals, and bacterial and protozoan teristics typical of invasive species and environ- contamination of soil and water are other con- mental weeds. Proença et al. (2015) reported on cerns regarding water quality (Hooda et  al., a production model that addresses some of these 2000). CAFOs present both potential benefits concerns about grassland ecosystem services. and threats to water quality. CAFOs confine live- The system of sown biodiverse permanent pas- stock waste, reducing the possibility of water tures rich in legumes has been successfully im- contamination over wide areas. However, failure plemented in Portugal on farms in Mediterranean of a containment facility can discharge large climate areas as a response to the low levels of quantities of waste in a matter of hours, over- productivity and feed quality obtained in whelming regular waste-management approaches semi-natural pastures. It consists of a mix of (Mallin and Cahoon, 2003). mostly local grasses and legumes, each mixture tailored to local environmental conditions to best cover the available environmental niches. The system combines higher pasture productiv- Air ity with soil carbon sequestration, reducing at- mospheric carbon dioxide (CO 2), providing the The most important air pollutants from livestock potential for increased farm income from pay- are emissions of GHGs. These are discussed in ments for soil carbon sequestration. 608 P. Ericksen, P. Thornton and G. Nelson Climate Change Impacts c ompared with crops (even fewer on fish and far on Ruminant Livestock fewer on pests and diseases). The major livestock-related climate impact Climate change affects livestock both directly messages from AR5 were as follows: and indirectly. The direct effects arise from • Temperature is an important limiting factor for higher temperature and humidity that slow livestock, for both meat and milk production. animal growth and increase susceptibility to dis- • Climate change will increase water stress ease. A recent study by Rose et al. (2014, p. 219) on livestock systems, affecting the water re- argued that ‘changes in climate’ may have a sources available for livestock via impacts ‘major impact on the seasonal transmission of on runoff and groundwater. gastro-intestinal nematodes in livestock’, based • Pasture response to climate change is com- on evidence from temperate and tropical condi- plex. Increases in CO2 concentration, tem- tions. Indirect effects are felt from the higher feed perature and precipitation will affect pas- prices that are likely as crop and pasture product- ture productivity and quality directly and ivity is reduced, changes in nutrient composition also have important indirect effects on of feeds and pastures occur, and climate affects plant competition, seasonal productivity livestock and wildlife pests and diseases. and plant–animal interactions. For example, AR5 highlighted that research on climate projected increases in temperature and the change impacts on livestock production systems lengthening of the growing season should was relatively limited at the time of its writing. extend forage production into late autumn ‘In comparison to crop and fish production, and early spring in temperate zones. In- c onsiderably less work has been published on creases in CO 2 will tend to benefit C3 species; observed impacts for other food production sys- however, warmer temperatures and drier tems, such as livestock or aquaculture, and to conditions will tend to favour C4 species. our knowledge nothing has been published for Often rangelands benefit from a combin- hunting or collection of wild foods other than for ation of both types of grasses as rainfall and capture fisheries’ (Porter et  al., 2014, p. 494). temperature vary throughout the year. Figure 16.1 shows one-seventh the number of • Host and pathogen systems in livestock will citations in Porter et  al. (2014) on livestock change their ranges because of climate (a) 300 (b) 300 200 200 100 100 0 0 ps ck ies es tio n tio n ge ilit y ’ o o n on ity ty r sto i i il ri C e he r s ea uc ibu a n b at at s h a c z a b i t cu Liv Fi s di ro d str cex for d llo til e d p di S s n : : y: : a f : a U d a lity ity ili t ss es s o i F o sts ab ab il ab e c ‘ Pe ai l ail va il Ac c Ac Av Av A Fig. 16.1. Livestock coverage in the ‘food security and food production systems’ chapter of AR5, Working Group II. (a) Subsectors, and pests and diseases; some citations are not mutually exclusive among categories (e.g. a few crop–livestock citations are included in both subsectors). (b) Food security dimensions. The category ‘Food security’ covers food security in general terms. (From Campbell et al., 2016.) Number of cited papers Number of cited papers Ruminant Livestock and Climate Change in the Tropics 609 change. Species diversity of some patho- role of livestock. Particularly in poor tropical gens may decrease in lowland tropical areas countries, livestock is an enormously import- as temperatures increase. For example, ant risk-management asset for hundreds of temperate regions may become more suit- millions of people. The impacts of increasing able for tropical vector-borne diseases such climate variability on downside risk and on the as Rift Valley fever and malaria. Vector-borne inter-annual stability of livestock production diseases of livestock such as African horse are not well studied. Jones and Thornton sickness and bluetongue may expand their (2009) provided some quantitative assessment range northwards to the northern hemi- of effects of climate change on livestock’s sphere. Changing frequency of extreme risk-management role. It is highly likely that weather events, particularly flooding, will the effects will be negative (Thornton and also affect diseases. Herrero, 2015). Table 16.2 gives AR5’s projected impacts of Climate change will affect all living organ- climate change on livestock in the tropics. At the isms, including livestock pests and diseases. The deadline for accepted papers for AR5 (August effects might be positive or negative for livestock 2013), detailed summaries of impacts on live- productivity depending on the biological suscep- stock systems with or without adaptation were tibility of the species to changes in temperature not available. Summaries addressing the inter- and humidity. The effects are likely to be location actions between crop and livestock enterprises specific and to vary over time as climate changes were also not available. become more pronounced. An important topic not covered in AR5 is how This research is in its infancy, but ILRI re- climate change might affect the risk-management searchers have been contributing to it since Table 16.2. AR5 livestock impacts in the tropics. (Adapted from Porter et al., 2014.) Region Subregion Climate change impacts Scenarios Africa Botswana Cost of supplying water from A2, B2, to 2050 boreholes could increase by 23% due to increased hours of pumping, under drier and warmer conditions Lowlands of Africa Reduced stocking of dairy cows, and a shift from cattle to sheep and goats, due to high temperature Highlands of East Livestock keeping could benefit Africa from increased temperature East Africa Maize stover availability per head of cattle may decrease due to water scarcity South Africa Dairy yields decrease by 10–25% A2, 2046–2065/2080–2100, ECHAM5/MPI-OM, GFDL-CM2.0/2, MRI-CGCM2.3.2 Central and Andean Mountain Beef and dairy cattle, pigs, and To 2060, hot and dry South countries chickens could decrease by scenario America between 0.9% and 3.2%, while sheep could increase by 7% Colombia, Venezuela Beef cattle choice declined To 2060, milder and wet and Ecuador scenario Argentina and Chile Beef cattle choice increased Future climate change Pernambuco, Brazil Milk production and feed intake in Future climate change cattle strongly affected 610 P. Ericksen, P. Thornton and G. Nelson the beginning of this century. McDermott Weather data in climate analyses et al. (2001) looked at the potential effects of climate change, human population growth An early step in research on climate change and and expected disease control activities on tse- its impacts was the release of MarkSim, a sto- tse distribution and trypanosomiasis risk in chastic weather generator developed at CIAT in five agroecological environments in sub- the 1990s in partnership with ILRI (Jones and Saharan Africa up to 2050. They found that Thornton, 1993, 1997, 1999, 2000). the combined effects of these changes would The livestock system classification of Seré be to contract areas under trypanosomiasis and Steinfeld (1996), further refined and devel- risk continent-wide with the greatest de- oped by Kruska et al. (2003), is driven partially crease in the impacts of animal trypanosom- by the length of growing period (LGP). The Mark- iasis in the semi-arid and subhumid zones of Sim model has since been used to refine models West Africa. of LGP. The early use of future LGP surfaces was More recently, Olwoch et al. (2008) exam- by McDermott et  al. (2001), who investigated ined effects of climate change on the range of the effects of climate, human population and the tick-borne disease East Coast fever in socio-economic changes on tsetse-transmitted sub-Saharan Africa using a species distribution trypanosomiasis to 2050. Another application model. They showed increases in East Coast fever of LGP surfaces was published as part of the suitability in the Northern Cape and Eastern study on ‘Mapping poverty and livestock in the Cape provinces of South Africa, Botswana, Ma- developing world’ (Thornton et al., 2002), which lawi, Zambia and eastern Democratic Republic had 479 Google Scholar citations to April 2020. of the Congo. The range shifts are due to changes Several projections have been made of how in temperature minima and maxima and in livestock systems might evolve by 2050 as cli- January and July rainfall. mate change affects LGP. Kristjanson et  al. Bett et al. (2017) reviewed case studies on (2004) projected LGP shifts and livestock system the epidemiology of infectious diseases. Some of changes in West Africa. They forecast declines the studies showed a positive association be- in LGP across most of West Africa, with many tween temperature and expansion of the geo- marginal cropping areas becoming even more graphical ranges of arthropod vectors, while marginal by mid-century and with rangeland others had a negative association. systems disappearing entirely in a few countries. Samy and Peterson (2016) used ecological Jones and Thornton (2009) (97th percentile in niche modelling with a comprehensive occur- Scopus citations) highlighted the possible liveli- rence data set to map the current distribution hood impacts of climate change across Africa, and explore the future potential distribution of hypothesizing that as cropping became more bluetongue virus globally under a range of cli- marginal in semi-arid zones, farmers would turn mate scenarios. Under future climate conditions, to more livestock keeping. the potential distribution of bluetongue virus MarkSim techniques were refined by was predicted to broaden, especially in Central Thornton et  al. (2006) on ‘Mapping climate Africa, the USA and western Russia. vulnerability and poverty in Africa.’ ‘Hotspots’ of climate change, identified via LGP changes projected to the middle of the 21st century for different global climate models and emissions CGIAR research on climate change scenarios, were combined with social indica- impacts in livestock systems tors to identify priority livestock systems for policies to reduce vulnerability and poverty. In the early 1990s, Philip Thornton of ILRI and The study concluded that many vulnerable Peter Jones of CIAT began two lines of research regions are likely to be adversely affected by cli- on climate change impacts and adaptation: mate change in sub-Saharan Africa, notably (i)  development of models to transform output the mixed arid–semi-arid systems in the Sahel, from climate models into weather data useful in the arid–semi-arid rangelands in eastern Africa, impact studies; and (ii) models of livestock sys- the Great Lakes and coastal regions of eastern tem performance under climate change. Africa, and all systems in southern Africa. Some Ruminant Livestock and Climate Change in the Tropics 611 of the maps and data from Thornton et  al. assessed potential priority activities for ILRI. The (2006) were used directly in the IPCC’s Fourth inventory of climate change impacts (Thornton Assessment Report (Boko et  al., 2007; IPCC, et al., 2009) listed seven topics – feeds quantity 2007) and the paper had been cited in Google and quality, heat stress, water quantity and Scholar more than 325 times to April 2020. quality, livestock diseases and disease vectors, Further analyses using MarkSim followed the biodiversity, systems and livelihoods, and indir- 2006 study. Projections of cattle trypanosomiasis ect impacts (human health effects from chan- were redone to 2030 for one of the UK Govern- ging disease burden, worsening heat-related ment’s Foresight Projects (Thornton et  al., mortality and morbidity). Table 16.3, adapted 2006). Systems impacts were analysed in Tur- from Thornton et al. (2008), summarizes gaps in kana District, Kenya (Notenbaert et  al., 2007). our understanding of the impacts of climate Impact studies were undertaken on pastoral and change and the role(s) that international re- agropastoral systems in East and West Africa for search might have in closing such gaps. the CGIAR’s Systemwide Livestock Programme Activities were ranked in relation to their (Thornton et al., 2008), and on the agricultural importance to ILRI’s mandate and the achieva- sector in East and Central Africa for the Associ- bility of outputs and outcomes. The top-ranked ation for Strengthening Agricultural Research in activities were: (i) identification of feed ‘hot- Eastern and Central Africa (ASARECA; van de spots’; (ii) improved understanding of climate Steeg et  al., 2009). Box 16.1 summarizes re- change on livestock systems and livestock keep- search utilizing MarkSim analysis and data gen- ers’ livelihoods; (iii) the development and deploy- eration. This list indicates the scope and nature ment of assessment frameworks and targeting of analyses completed, with impacts on crop and tools; and (iv) identification and dissemination livestock productivity, pest incidence, changes in of adaptation options. In the 10 years since the land use, CH emissions and poverty. Rassmann analysis was completed, considerable progress 4 and Schuetz (2017) highlighted wider studies has been made in activities (ii) and (iii). Less pro- using MarkSim, including a study on the pos- gress has been made on activities (i) and (iv), al- sible future spread of the Zika virus (Messina though new research is under way at ILRI on et al., 2016) and a projected decline in ice-skating both of these areas. days in Canada, an important recreational eco- ILRI inputs were used in the International system service in that country (Brammer et  al., Assessment of Agricultural Knowledge, Science 2015). and Technology for Development (IAASTD) A recent innovation promises to expand agricultural scenarios to 2050 (Rosegrant et al., MarkSim’s usefulness. MarkSim/GCM is a web 2009), which projected spatial livestock data. tool that uses MarkSim to generate location- Reception of the IAASTD report at its release specific weather data from GCM results used in was mixed, although it did provide an important AR5. The outputs include graphical depictions analysis of necessary changes in the global food of the data and creation of a data set that can be system. ILRI work has also contributed to the imported into the crop modelling software DSSAT. analysis of drivers of change in agricultural sys- (http://gisweb.ciat.cgiar.org/MarkSimGCM/; tems (van Vuuren et al., 2009). accessed 7 March 2020). The second version of Box 16.2 summarizes key ILRI research MarkSim will be improved over the first version outputs on climate change impacts, including as it will use 55,000 rainfall stations, compared reviews of impact and adaptation studies in with some 9000 for version 1. It will allow the mixed crop–livestock and pastoral–agro-pastoral study of novel climates – climates that will exist systems and a range of adaptation studies using in the future that currently do not exist any- different modelling approaches at varying scales where – in more detail. (e.g. household, regional, global). Tables 16.1 and 16.2 highlight the shift from livestock com- ponent impact studies to more systems-oriented Impacts on livestock systems work that attempts to understand the broader implications of climate change adaptation at dif- Thornton et  al. (2008) reviewed what was ferent scales. Much of the research of ILRI and known about climate change and livestock and its partners is tied to models of sustainable 612 P. Ericksen, P. Thornton and G. Nelson Box 16.1. Impact of the MarkSim model. MarkSim has had far-reaching impacts in: (i) modelling crop production; (ii) mapping the relationships among climate, agriculture and poverty; and (iii) modelling system effects of climate change: Modelling crop production Impacts of climate change to 2055 on maize yields in Latin Jones and Thornton (2003) (99th America and Africa percentile in Scopus) Spatial variation of crop yield response to climate change in Thornton et al. (2009) (99th East Africa percentile in Scopus) Rainfall variability, and impacts of climate change on length Thornton et al. (2007) of growing period Mapping relationships among climate, agriculture and poverty Mapping poverty and livestock in the developing world Thornton et al. (2002) Mapping climate vulnerability and poverty in Africa Thornton et al. (2006) The livestock, climate change and poverty nexus Thornton et al. (2008) Modelling system effects of climate change Effects of climate, human population and socio-economic McDermott et al. (2001) changes on tsetse-transmitted trypanosomiasis to 2050 Livestock systems changes to 2050 in West Africa Kristjanson et al. (2004) Cattle trypanosomiasis in Africa to 2030 Thornton et al. (2006) Livestock development and climate change in Turkana Notenbaert et al. (2007) District, Kenya Impacts of climate change on pastoral and agropastoral Thornton et al. (2008) systems in East and West Africa Understanding climate–land interactions in East Africa Olson et al. (2008) Spatial distribution of CH4 emissions from African domestic Herrero et al. (2008) ruminants to 2030 Influence of climate change and climate variability on the van de Steeg et al. (2009) agricultural sector of East and Central Africa Livestock system impacts in the tropics Thornton and Herrero (2010a) Climate change and crop production impacts in Thornton (2009) the Albertine Rift Possible impacts of climate change on livelihood transitions Jones and Thornton (2009) in Africa – croppers to livestock keepers? Adapting to climate change in households in East Africa at Thornton et al. (2010) the level of the household and the system Impacts of climate change on migration to 2060 New et al. (2011) Mapping hotspots of climate change and food insecurity in Ericksen et al. (2011) the global tropics Adapting to climate change in mixed crop–livestock systems Thornton et al. (2011) in developing countries Agriculture in sub-Saharan Africa in a 4°-plus world Thornton et al. (2011) Global livestock production systems Robinson et al. (2011) Consequences of climate change for pastoralism in Ericksen et al. (2012) sub-Saharan Africa Future climate change and land-use change impacts on East Moore et al. (2012) African food security MarkSim as a GCM downscaling tool: AR4 climate model Jones and Thornton (2013) ensembles Climate change adaptation in mixed crop–livestock systems Thornton and Herrero (2015) in developing countries Climate variability and vulnerability to climate change: a Thornton et al. (2014) review Continued Ruminant Livestock and Climate Change in the Tropics 613 Box 16.1. Continued. Impacts on smallholder agriculture in sub-Saharan Africa to Cooper et al. (2014) 2050 Climate change impacts on livestock Thornton et al. (2015) Carbon and biodiversity costs of converting Africa’s wet Searchinger et al. (2015) savannahs to cropland MarkSim as a GCM downscaling tool: AR5 climate model Jones and Thornton (2015) ensembles and soils data Climate change adaptation in the mixed crop–livestock Thornton and Herrero (2015) system in sub-Saharan Africa Adaptation paths for vulnerable areas Cacho et al. (2016) Pastoral farming systems and food security in sub-Saharan de Leeuw et al. (2019) Africa i ntensification (Garnett et al., 2013) and climate- variability, more information is needed concern- smart agriculture (Lipper et al., 2014). ing the nature and extent of the trade-offs among crop and livestock enterprises, and be- tween on- and off-farm income sources, as cli- Current knowledge gaps on impacts mate variability increases. This may have critical effects on food security; in addition to impacts on As initially identified by Thornton et al. (2008), food availability, variability may strongly affect identification of feed ‘hotspots’ remains a priority. the stability of food supplies and vulnerable In addition, there is much that is not well under- people’s ability to access food at affordable prices stood about the interactions of climate and cli- (Schmidhuber and Tubiello, 2007). Key to these mate variability with other drivers of change in broad issues will be the refinement of impact livestock systems and with population growth, models to assess climate variability effects on income growth and global trade. Multiple and adaptation and mitigation options at regional competing pressures are likely on tropical and and local scales, their effects on livelihoods and subtropical livestock systems in the future, to the trade-offs that arise among income, food se- produce food, to feed livestock and to produce curity and environmental objectives. energy crops, for example. While recent scien- Grace et al. (2015) identified the following tific assessments such a AR4 and AR5 (IPCC, knowledge gaps in animal disease and climate 2007, 2014) represent an accurate reflection of change: current knowledge, there remain gaps in their treatment of tropical livestock systems regard- • Information on animal diseases. The rela- ing the provision of ecosystems goods and ser- tively limited availability of epidemiological vices and the maintenance of livelihoods. (and ecological) observations on animal First, more clarity is needed concerning the disease in the tropics constrains our under- benefits of livestock, their negative impacts on standing of the climate–disease relation- GHG emissions and the environment, and the ef- ships. Current surveillance detects only a fects of climate change on livestock systems. The small proportion of livestock and wildlife regional and local variations in public costs and diseases and is not well linked to human dis- benefits associated with livestock need to be ease surveillance. understood before technology and policy op- • Disease dynamics. There are numerous tions for adaptation and mitigation can be tar- pathways – direct and indirect – through geted appropriately. Much agricultural impact which climate can influence disease. These work is reported at a continental or regional drivers are not all equal, and impacts medi- level (e.g. Lobell et al., 2008), but this aggrega- ated through changes in human popula- tion masks widespread differences. tion and behaviour may induce effects that Second, while a great deal is known about are orders of magnitude greater than those how livestock keepers manage current climate mediated through biological pathways. 614 P. Ericksen, P. Thornton and G. Nelson Table 16.3. Climate change knowledge gaps and research hypotheses. (Adapted from Thornton et al., 2008.) Feasibility of Alternative delivery Regional System Time to suppliers Feasibility of (outputs to Activity area Knowledge gaps Research outputs focus focus outputs Relative cost of outputs outputs outcomes) Feeds: What are the Localized impacts East, West MRA, LRA Short Low Very few High High (e.g. for quantity localized and hotspots and South priority and quality impacts? identified Africa setting) Rangelands: primary Rangeland net East and LRA/LRH/ Medium Medium ARIs Medium–high Medium productivity, primary South LRT species productivity Africa, distribution and distribution and North-east change due to impacts Asia CO2 and other elucidated factors; estimation of carrying capacities Crops: primary Modified crop and East, West MRA/MRH/ Long Medium–high Very few Medium Low–medium productivity, residue quality and South MRT, harvest indexes and quantity Africa, MIA/MIH/ and stover South Asia MIT production, dual purpose crops Feasibility of new New feeding East, West MRA/MRH/ Medium–long Medium NARS Medium Low–medium feeding strategies strategies and South MRT with existing developed Africa, materials South Asia Pests and diseases Hotspots identified East, West MRA/MRH/ Medium Medium OIOs Low–medium Medium of feeds of key pests, and South MRT diseases of key Africa feed crops Water Evolution of surface Understanding of East, West LRA/LRH/ Medium Medium OIOs Low–medium Medium and groundwater changes in and South LRT, supply, impacts surface and Africa, MRA/ on livestock groundwater South Asia MRH/ supply, and MRT impacts on livestock Ruminant Livestock and Climate Change in the Tropics 615 Increases in Options East, West LRA/LRT, Medium–long Medium–high Very few Low–medium Medium livestock water developed and and South MRA/ productivity tested to Africa, MRT, increase South Asia MIA/MIT livestock water productivity Animal Potential changes in Future changes in East, West All livestock Medium–long Medium–high ARIs Low–medium Medium–high health the prevalence prevalence and and South systems and intensity of intensity of Africa, epizootics in epizootics South Asia livestock predicted Impacts of diseases Impacts of East, West MRH/MRT, Medium–long Medium–high OIOs Low–medium Medium–high of intensification ‘management’ and South coast, (e.g. mastitis) diseases Africa, urban elucidated and South Asia options identified Biodiversity ‘Ecological Impacts on East, West All livestock Medium–long Medium–high GCC Low Low biodiversity’: what ecological and South systems will happen to biodiversity Africa, numbers of elucidated South Asia species as systems change? Animal breed Animal breed East, West All livestock Medium–long High OIOs Low High biodiversity: which biodiversity and South systems traits might be characterized, Africa, useful in the and a road South Asia future? map developed for future exploitation Plant biodiversity: Animal breed East, West All livestock Medium–long High OIOs Low High which traits and biodiversity and South systems hence which characterized, Africa, germplasm might and a road South Asia be useful in the map developed future? for future exploitation ARI, advanced research institute; GCC, global change community; LRA, livestock/rainfed/arid; LRH, livestock/rainfed/humid; LRT, livestock/rainfed/temperate and tropical; NARS, national agricultural research system; OIO, other international organization. 616 P. Ericksen, P. Thornton and G. Nelson Box 16.2. Impact of ILRI climate research. Climate research by ILRI and partners has had important scientific impacts on: (i) policy options; (ii) mitigation technologies; (iii) adaptation problems; and (iv) the future of tropical agriculture. Policy options Livestock production: recent trends, future prospects Thornton (2010) (99th percentile in Scopus) Discussion paper on ILRI’s research in relation to climate change Thornton et al. (2008) A review of the impacts of climate change on livestock and livestock Thornton et al. (2009) systems in developing countries, current knowledge and gaps Coping with drought and climate change in the pastoral sector in sub- Herrero et al. (2010) Saharan Africa: policy considerations Livestock and global change: emerging issues for sustainable food systems; Herrero and Thornton a brief summary of the major challenges (2013) Livestock contributions to the chapter ‘Food Security and Food Production Porter et al. (2014) Systems,’ Working Group II Livestock and the environment: what have we learnt in the last decade? Herrero et al. (2015) Impacts of climate change on the agricultural and aquatic systems and natural Thornton and Cramer resources within CGIAR’s mandate: an inventory of what is known (2012) How does climate change alter agricultural strategies to support food Thornton and Lipper security? (2014) Mitigation technologies The potential for reduced CH4 and CO2 emissions from livestock and Thornton and Herrero pasture management in the tropics; analysis based on systems (2010b) characterization in the future The impacts of climate change on livestock and livestock systems in Thornton et al. (2010) developing countries Adaptation problems Is proactive adaptation to climate change necessary in grazed rangelands? Ash et al. (2012) A study on how these systems may need to adapt Adapting smallholder mixed crop–livestock farming systems to climate Rigolot et al. (2017) variability in northern Burkina Faso with crop–livestock interactions Transitions in agro-pastoralist systems of East Africa: impacts on food Rufino et al. (2013) security and poverty. Twelve case study sites in the marginal areas, evaluating likely impacts and possible adaptations Evaluating climate-smart adaptation options in mixed crop–livestock Thornton et al. (2016) systems in developing countries: a largely qualitative approach to targeting and evaluation Climate change and pastoralism: impacts, consequences and adaptation Herrero et al. (2016) Exploring future changes in smallholder farming systems by linking Herrero et al. (2014) socio-economic scenarios with regional and household models: an early multi-scale analysis of different drives of change, including climate change The future of tropical agriculture The future of agriculture (crops and livestock) to 2050 Rosegrant et al. (2009) Drivers of change in agricultural systems to 2050 van Vuuren et al. (2009) A largely qualitative assessment of the likely effects of climate change as a Thornton and Gerber constraint to the growth of the livestock sector (2009) Kenya: climate variability and climate change and their impacts on the Herrero et al. (2010) agricultural sector Implications of future climate and atmospheric CO2 content for regional Doherty et al. (2010) biogeochemistry, biogeography and ecosystem services across East Africa Climate change and the growth of the livestock sector in developing countries Thornton and Gerber (2009) Impact of climate change on African agriculture: focus on pests and diseases Dinesh et al. (2019) Using a stakeholder and multi-model process to translate the shared Palazzo et al. (2017) socio-economic paths under climate change for the West Africa region Ruminant Livestock and Climate Change in the Tropics 617 • Multi-host diseases. The majority of climate- Improving livestock genetics is an option. sensitive diseases affect many host species Ortiz-Colón et al. (2018) reviewed work from the including livestock, wildlife and occasionally Caribbean showing that introducing a ‘slick humans. This makes them much more diffi- hair’ gene into Holstein cows by cross-breeding cult to control or eliminate than disease that with Senepols may increase heat tolerance and have only a human or livestock host (for ex- productivity. However, genetic improvements ample, when zoonotic tuberculosis is present would require substantial investments and in badgers it is much more difficult to control would involve long delays before being intro- than when it is only present in cattle). duced into production animal populations. • Joint occurrence of climate-sensitive dis- Moreover, there would be temperature limits eases. A review of risk maps reveals that a above which adaptation is not possible, even number of climate-sensitive livestock dis- with substantial genetic progress. eases occur in some common areas given that their emergence and transmission are controlled by similar ecological factors. Costs of adaptation • Lack of laboratory and epidemiology cap- acity. The lack of laboratory and epidemi- There are many possible adaptations in tropical ology capacity is a long-standing problem livestock systems for which we lack informa- in developing countries. Much effort and tion on social and private costs and benefits. expense has been spent on improving cap- Dittrich et  al. (2017) suggested techniques to acity, and best approaches exist but require assess livestock adaptations, such as cost– investment. benefit analysis, portfolio analysis, real options analysis and robust decision making, but their approach suffered from a lack of empirical data Adaptation of Livestock Systems to verify the proposed adaptations under trop- to Climate Change ical conditions. Weindl et  al. (2015) is the only study to project adaptation costs by simulating climate The AR5 text (IPCC, 2014) on adaptation re- impacts on crop and range yields productivity lies heavily on Thornton et al. (2009) for its list for ten world regions to 2045. If tropical live- of adaptation options. Adaptation options in- stock systems shift towards mixed crop–live- clude: (i) matching stocking rates with pasture stock systems and away from grazing systems, production; (ii) adjusting herd and watering adaptation costs would fall in sub-Saharan Af- point management to altered seasonal and rica and Latin America and the Caribbean, spatial patterns of forage production; (iii) man- while rising significantly in Pacific Asia and aging diet quality (using diet supplements, leg- South Asia. The Weindl model does not ac- umes, introduced pasture species and pasture count for climate change effects on livestock fertility management); (iv) more effective use disease or on animal reproductive performance of silage, pasture seeding and rotation; (v) fire and it is likely, therefore, to underestimate management to control browse encroachment; adaptation costs. (vi) using more suitable livestock breeds or spe- cies; (vii) migratory pastoralism; and (viii) bios- ecurity activities to monitor and manage pests, weeds and diseases (IPCC, 2014, p. 517). CGIAR research on climate change Research in Australia found that combin- adaptation in livestock systems ing adaptations can be more beneficial than sin- gle adaptations (Ghahramani and Moore, 2013; While there have been extensive international Moore and Ghahramani, 2013). Options in- efforts to develop options to adapt to climate clude replacing cattle with small ruminants, re- change, less has been done with producers on ducing stocking rates, better water management implementation of these options. One innov- technologies and animal health services, and ation with the potential to facilitate adaptation improving tree cover. has been agricultural insurance. 618 P. Ericksen, P. Thornton and G. Nelson The information costs and incentive prob- A challenge to any insurance approach is lems that are characteristic of agriculture have cost. While it is conceptually possible for an insur- often prevented the emergence of insurance ance scheme to self-finance, and many private in- markets in rural areas (Binswanger and Rosenz- surance programmes do so in other markets (e.g. weig, 1986). As information costs have fallen, life, automobile, health insurance) because of the use of insurance for agricultural risk man- long experience identifying actuarial risks, agri- agement has become more common in devel- cultural insurance markets have proven difficult oped countries for staple crops (e.g. maize, for the private sector to operate profitably because wheat) and to a lesser extent for other crops and of the spatial nature of agriculture. The spatial livestock. Insurance, by managing the effects of nature of farming makes it costly to monitor risks shocks, allows farms to invest more profitably in and identify losses that trigger payment. Further- non-shock periods (Alderman and Haque, 2007; more, climate change is likely to change the risk Barnett et al., 2008; Mahul and Stutley, 2010). portfolio in unknown ways, making insurance Insurance also facilitates complementary mar- management more difficult. kets, such as those for credit, inputs and produc- tion methods (Alderman, and Haque, 2007; Carter et al., 2007) by diffusing risks. Insurance can potentially help farmers to manage climate Knowledge gaps on adaptation risk by allowing them to use new adaptation strategies, while reducing the adverse effects of Thornton et  al. (2008) summarized the know- current shocks (Collier et al., 2009). ledge gaps in adaptation and followed a priority- Index insurance has emerged as a possible setting process to identify adaptation activities solution for overcoming supply-side constraints by their importance to ILRI’s mandate, the clar- to rural insurance markets and for extending ity of ILRI’s role, the presence of other providers, access to agricultural insurance. The Index- the achievability of outputs and outcomes, and based Livestock Insurance (IBLI) work is one the cost and approximate time to output. The form of that solution. By basing insurance pol- gaps were as follows icies on easily observed indices, such as precipi- tation or temperature, that are covariate with • Adequately detailed estimates of the impacts rural income and wealth risks, index insurance of climate change on livestock systems with can potentially resolve the information costs or without adaptation. and incentive problems inherent in rural finan- • The impacts of increasing climate variability. cial markets and allow provision of insurance • Information on costs and benefits of adap- coverage at a fraction of the costs of loss-based tations at given sites and seasons. This ap- polices (Chantarat et  al., 2013; Jensen and plies particularly to mixed systems, in Barrett, 2016). which the interactions between crops and There is some limited empirical evidence livestock can sometimes be managed to ad- of the effects of IBLI. Households with IBLI vantage. The challenge is to target packages coverage reduced their herd size and increased of adaptation options that are locally ap- investments that made the remaining animals propriate and amenable to scaling up. more productive (Thornton and Herrero 2010; Some of the major gaps were addressed in Gerber, et al., 2011; Jensen et al., 2017). Such the decade since Thornton et al. (2008). One ex- impacts are consistent with economic theory, ample was the impacts of climate change on whereby insurance coverage substitutes for rangeland net primary productivity (Boone et al., informal insurance mechanisms, oversized 2018). Several assessment models and targeting herds in this case. Insurance releases house- tools were developed and a special issue of Agri- holds from some risk constraints so that they cultural Systems (Volume 151, February 2017) can invest in productivity-increasing tech- was devoted to this topic. However, while these nologies, such as animal health care. In terms studies provide insights into what the impacts of of climate change adaptation, insurance re- climate change are likely to be, they do not pro- duces sensitivity to drought and lowers the vide much general guidance on priority adapta- costs of adaptation. tion activities as these are context s pecific. Ruminant Livestock and Climate Change in the Tropics 619 A review by Ash et al. (2012) gave mixed results However, the most recent epoch in which global about the need for ‘proactive adaptation’ in temperature was as high as it is now was more rangelands; while ‘incremental, autonomous than 100,000  years ago. The experiences of adaptation [would be] sufficient to deal with the pastoralists in recent millennia may therefore gradual expression of climate’ it is not known prove inadequate for adapting to current how autonomous adaptation can manage more changes in levels and variability of temperature rapid climate change in the absence of new re- and humidity. For example, Thornton and search and more supportive public policies. Herrero (2010a) simulated an increase in drought frequency to once every 3  years and Adaptation in mixed crop–livestock found that this higher frequency decreased live- systems stock densities below desirable levels. In some places, adaptation will be possible through spe- Thornton and Herrero (2015) highlight four re- cies changes, increased market orientation or search needs for appropriate adaptation options the increased ability of pastoralists to manage among mixed crop–livestock enterprises in climate risk. sub-Saharan Africa: Increasing population densities can rapidly 1. Biophysical models are needed to represent modify the accessibility to land, water and feed interactions among crops and livestock to make that makes pastoralism a viable livelihood strat- evaluations of mixed systems more robust. Most egy (Hobbs et al., 2008). Rising incomes are af- biophysical modelling has been done on the pri- fecting consumption patterns and modifying mary cereals (particularly maize, rice and expectations, with lasting impacts on traditional wheat) and legumes (groundnut and soybean), socio-cultural value systems and kinship net- but more work is needed on lesser-studied crops, works. In some places, adaptation will be pos- such as trees and other perennials. sible via farming system intensification through 2. Whole-farm models are needed because of increased market orientation and increased abil- the complex interactions of financial and phys- ity of pastoralists to manage climate-related ical resources in smallholder households. Trade- risks. In others, adaptation may need to be more offs between benefits and costs of adaptation transformative, including social innovations recommendations are inevitable and must be and changes in behaviour, institutions and cul- quantified with a whole-farm perspective. Whole- tural norms. Opportunities exist for improving farm modelling, especially in tropical A frica, is development outcomes in pastoral systems, constrained by a systemic lack of time-series through combinations of policies and institu- data. The explicit inclusion of human nutrition tional and technological alternatives that will with its appropriate metrics is also essential. vary with context and through time as the fu- 3. Use of future scenarios is needed to capture ture climate change envelope becomes less un- the nuances of smallholder systems in the con- certain (Ericksen et  al., 2012). Understanding text of larger economic and biological changes. what is possible, what is not, and where will be Some smallholder systems will intensify produc- critical for effectively improving the livelihoods tion and survive; others will become redundant of pastoralists and their rangelands (Herrero as smallholdings are aggregated into larger, more et al., 2016). intensive and more specialized systems. Research is also needed on how policy can 4. Better metrics are needed to estimate vulner- support the scaling of interventions that can ability to climate change among smallholders contribute to food and nutritional security and and to define measures of successful adaptation, poverty reduction under climate change. ILRI is such as sustainability and reduced variability of already contributing to this agenda via work on income. IBLI and cash transfers and research on effect- ive governance mechanisms that can promote adaptation. A recent collaboration with the Adaptation in pastoral systems World Agroforestry Centre called Local Govern- ance and Adaptation to Climate Change (LGACC; Pastoralists have long adapted to a highly vari- http://www.worldagroforestry.org/project/ able climate (see Chapter 15, this volume). local-governance-and-adapting-climate-change- 620 P. Ericksen, P. Thornton and G. Nelson sub-saharan-africa-lgacc; accessed 8 March agricultural emissions estimates of between 2020), for example, combined research on 4.25 and 5.25 GtCO2eq/year (Smith et al., 2014, rangeland governance with research on pro- Fig. 11.4). Estimates of emissions from enteric cesses that promote adaptation. The team was fermentation were just less than 2 GtCO2eq/year, able to draw conclusions about the comple- implying that cattle were responsible for 40–50% mentarity between governance, rangeland of agricultural emissions. Figure 16.2 reports management and climate change adaptation early 21st century estimates of anthropogenic (LGACC, 2018). GHG emissions and livestock’s share. In this fig- ure, livestock’s share of total emissions is 14.5%, with 27% from CO2, 29% from N2O and 44% Mitigation of Greenhouse Gas from CH4. Figure 16.3 shows the spatial distri- Emissions from Livestock bution of livestock GHG emissions around the turn of the century. National research on livestock emissions has The livestock sector is a major source of GHG been growing rapidly in response to the United emissions, primarily CH4, CO2 and N2O. Emis- Nations Framework Convention on Climate sions arise from five components – ruminant Change (UNFCCC) requirement of national emis- digestion, excretion of manure and urine, feed sions inventories. Patra (2012) estimated CH production, land conversion to pasture and 4and N2O emissions from Indian livestock. Svinurai transport/processing. et  al. (2018) provided estimates of enteric CH Projections from the beginning of the 21st 4emissions in Zimbabwe. What is not clear is how century to mid-century suggest that per capita comparable the country-specific results are. The meat consumption between 2010 and 2050 Standard Assessment of Agricultural Mitigation could increase by about 50% for low-income Potential and Livelihoods (SAMPLES) project countries and about 10% for higher-income coun- (http://samples.ccafs.cgiar.org; accessed 8 March tries (Nelson et al., 2018, Supplementary Fig. 4). 2020) of which ILRI researchers are a part is de- Low- and middle-income countries have a 62% signed to facilitate this cross-country comparabil- share of total global production, rising to 72% by ity (Rosenstock et al., 2016). 2050 (Thornton, 2010). The GHG mitigation challenge is how to satisfy a growing livestock product demand while reducing GHG emissions. Mitigation via supply- and demand-side options Estimates of emissions from livestock Supply-side activities to reduce GHG emissions from ruminant livestock production can be clas- Estimates of GHG emissions of livestock prod- sified as: (i) targeting reductions of enteric CH4; ucts vary considerably; emissions per unit of (ii) managing manure to reduce N2O emissions; protein are highest for beef and dairy and lower (iii) sequestering carbon in rangelands; (iv) im- for pork, chicken meat and eggs (de Vries and de plementation of better animal husbandry prac- Boer, 2010; Gerber et al., 2013) due to their dif- tices; and (v) land-use practices to sequester ferent feed and land-use intensities. Beef pro- carbon. Excluding land-use practices, Herrero duction can use up to five times more biomass to et al. (2016) found that these options have a glo- produce 1 kg of animal protein than dairy. Emis- bal mitigation potential of 2.4  GtCO2eq/year. sions intensities for the same livestock product These estimates are in the same range as those also vary largely among different regions of the proposed by Gerber et al. (2013) of 1.8 GtCO2-eq/ world (Herrero et al., 2013). Europe and North year, although strategies will vary by production America have lower emission intensities per kg system (Rivera-Ferre et al., 2016). of protein than Africa, Asia and Latin America. The AR5 review of mitigation options in Estimates of the contribution of livestock to agriculture (Smith et al., 2014) found that: GHG emissions depend on estimation methods Studies based on integrated modelling show that and data sources. AR5 reported a range of total changes in diets strongly affect future GHG Ruminant Livestock and Climate Change in the Tropics 621 Global total GHG anthropogenic emissions 27% CO2 29% N2O 44% CH4 Livestock contributes Livestock contributes Livestock contributes 5% 53% 44% 1.35% of total CO2 15% of total N2O 19% of total CH4 anthropogenic emissions anthropogenic emissions anthropogenic emissions 25 times CO 298 times CO 22 14.5% of total GHG anthropogenic emissions Fig. 16.2. Global total GHG anthropogenic emissions and livestock’s share. (From Rojas-Downing et al., 2017, based on analysis for the early 21st century in Gerber et al., 2013.) MtCO2eq/km 2/year 7.5 15 30 45 60 75 90 105120 Fig. 16.3. GHG emissions from global livestock, 1995–2005. (From Herrero et al., 2016.) emissions from food production… Technical changes in consumption was found to be mitigation options on the supply side, such as substantially higher than that of technical improved cropland or livestock management, mitigation measures. alone could reduce [emissions from 15.3 GtCO2eq/year] to 9.8 GtCO2eq/yr, whereas emissions were reduced to 4.3 GtCO eq/yr in a Supply-side options2 ‘decreased livestock product’ scenario and to 2.5 GtCO eq/yr if both technical mitigation and Supply-side efforts have focused on reducing the 2 dietary change were assumed. Hence, the GHG burden of livestock through increases in potential to reduce GHG emissions through productivity. Capper et  al. (2009) showed that 622 P. Ericksen, P. Thornton and G. Nelson US dairy production in 2007 used only 21% of achieved if reduced consumption of animal- the animals, 23% of the feed, 35% of the water based products is combined with sustained and 10% of the milk that had been required in productivity gains in plant production, but the 1944 to produce 1 billion kg of milk. Emissions economic feasibility of the latter is uncertain. from dairy cattle fell in consequence, with CH4 Scherer and Verburg (2017) compared emissions only 43% and 56% of N2O emissions supply- and demand-side options under the in 2007 relative to 1944. Overall, the carbon- label of ‘climate-smart agriculture’. Adaptation equivalent footprint of 1 billion kg of milk in the measures under climate-smart agriculture can USA in 2007 was 34% of that in 1944. Similar involve technological advances, new farming evidence was found by Gerber et al. (2011) who practices, and changes in food origin and supply identified four reasons for the reduction in emis- chain management. Unlike Weindl et al. (2017), sions from dairy systems as they intensify: (i) Scherer and Verburg (2017) did not use an inte- higher-quality diets; (ii) higher proportions of grated global model, so their findings are weaker feed energy and protein used for production and with regard to demand-side measures. Their not maintenance; (iii) higher nitrogen efficiency; findings were that: (i) emissions reductions are and (iv) a concentration approach to reducing possible with demand measures, such as a vegan unit emissions through genetics and animal diet or local sourcing, but their economics are health. very uncertain and site-specific; and (ii) supply- Gerber et al. (2013, p. xiii) provided a global side measures can also have mitigation effects, review of mitigation potentials to reduce GHG but the latter are probably less effective than emissions from ruminant and non-ruminant demand measures. livestock. They found that a ‘30% reduction of Ripple et al. (2013) argued for both supply- GHG emissions would be possible, for example, if and demand-side options, citing modelling of a producers in a given system, region and climate food tax proportional to the mean GHG emis- adopted the technologies and practice currently sions per unit of food sold. Shields and Orme- used by the 10% of producers with the lowest Evans (2015) argued that a mitigation strategy emission intensity’. of intensifying production would not be socially The technical changes modelled in Gerber sustainable because of its adverse effects on ani- et al. (2013) are due to productivity gains from mal welfare. higher digestibility feeds, herd health interven- Valin et  al. (2013) reported results from tions and genetic selection for animals with GLOBIOM modelling of productivity increases in higher milk productivity. It is not clear whether crops and livestock. They found that closing the technologies producing these gains are yield gaps by 50% for crops and 25% for live- profitable. stock by 2050 would decrease agriculture and Weindl et al. (2017) compared supply- and land-use change emissions by 8% overall, and by demand-side scenarios in carbon dynamics to 12% per calorie produced. However, the out- 2050. They mapped the results of two demand come is sensitive to the technological path and scenarios – a continuation of trends in global which factor benefits from productivity gains: diets, including levels of animal products, and a sustainable land intensification would increase gradual change in diet projections to lower GHG savings by one-third when compared with shares of animal-based calories in diets, with a fertilizer-intensive pathway. Improvements in 15% as the upper limit in 2050 for calories from the crop or livestock sector have different out- livestock and fish – and four supply scenarios, comes: crop yield gains would bring the largest ranging from current levels of productivity in food provision benefits, whereas livestock yield low-productivity animal systems to slight to low gains would bring the largest cuts in GHGs. to moderate productivity gains. Changes in diet N 2O is a powerful GHG that is emitted as a would produce substantial reductions in CO 2 consequence of the use of both organic and in- burden at all levels of productivity change, ran- organic nitrogenous fertilizers. Some quantity ging from –40% to –57%. Changes in productiv- of applied nitrogen is not taken up by the plants ity without changes in diet would increase the and is lost to ground water and the atmosphere. CO2 burden substantially. The highest abate- In the early part of the 21st century, it was dis- ment of carbon emissions (63–78%) can be covered that the roots of many plants release Ruminant Livestock and Climate Change in the Tropics 623 substances that inhibit nitrogen release. The i ncrease to meet demand and using data from process is called ‘biological nitrification inhib- FAO on livestock species and diet composition ition’. Early research focused on the tropical pas- and Food and Agriculture Organization Corpor- ture grass, Brachiaria spp., and researchers have ate Statistical Database (FAOSTAT) population since looked into the possibility of enhancing projections. For the latter, Africa was divided biological nitrification inhibition in wheat, bar- into regions to be more specific about diets by ley and rye (Subbarao et al., 2009; Moreta et al., production system and season variation, along 2014; Byrnes et al., 2017; Karwat et al., 2017; with the level of intensification. To move from Subbarao et  al., 2017; Nuñez et  al., 2018; diets to CH 4 emissions, they used the RUMIN- Teutscherova et al., 2019). ANT model. The results showed the importance of the assumptions about population growth and Mitigation research in livestock systems changes in densities, as these drove the pro- jected increase in total CH4 emissions, estimated A key contribution to both ILRI and other re- to be 42% between 2000 and 2030. Emissions searchers in the study of livestock emissions was intensities differed between production systems, the development of the RUMINANT model, as but all were estimated to increase by 2030. first described by Herrero (1997) and subse- Total emissions varied by region, with the Horn quently by Herrero et al. (2013), with reference of Africa estimated to be the largest emitting re- to Sniffen et  al. (1992) and AFRC (1993). It is gion. Cattle contributed over 80% of emissions used to predict feed intake, nutrient supply and across the continent. These findings were in line CH emissions. These numbers are then aggre- with other studies. Steinfeld et  al. (2006) esti-4 gated to systems, countries, regions and contin- mated emissions from Africa to be about 13% of ents using the population projections. the global total of enteric CH4; Herrero et  al. The main mitigation research at ILRI began (2008) estimated the contribution to be about just after the publication of Livestock’s Long 10%. The differences are due largely to assump- Shadow (Steinfeld et al., 2006), building on earl- tions and inherent uncertainties in emissions ier research at ILRI on five factors – digestion, factor estimates, which suggested the need for manure, feed production, land conversion and more research to have better CH4 emissions esti- transport/processing – that contribute to rumi- mates and targeting of interventions to reduce nant-related GHG emissions. The goal was to emissions. develop spatially disaggregated livestock system In 2009, the IPCC GHG emissions taskforce data and better information on differential im- invited ILRI’s contribution to the emissions fac- pacts and emissions by system, species, region, tor database. ILRI’s contributions included both technology and country. biological research into emissions from cattle Herrero et  al. (2008) published the first production systems (e.g. Pelster et al., 2016) and study estimating emissions from African domes- a long-term collaboration with the GLOBIOM tic ruminants. This study combined country- model at IIASA. level calculations of changes in livestock Thornton and Herrero (2010b) estimated production due to population densities and cli- the potential for four interventions to reduce mate change with spatially explicit distributions GHG emissions from livestock: (i) adoption of of CH 4 emissions. The classification system built improved pastures; (ii) intensification of rumin- upon earlier ILRI efforts to better classify and ant diets; (iii) changes in land-use practices; and map livestock production systems (Kruska et al., (iv) changing breeds of ruminants. They esti- 2003; Kruska, 2006), accounting for differences mated reductions in emissions intensities, per in land areas, population densities, numbers of unit of milk or meat, and reductions in numbers livestock and diets for ruminants. Climate of animals (e.g. from improved productivity), as change was modelled as changes in LGP using well as carbon sequestered through the land the MarkSim model, which resulted in changes management options. Restoration of degraded in area under different production systems rangelands had the highest mitigation potential, (Thornton et al., 2006). For animal population followed by agroforestry, which both sequesters changes, national projections were made as- carbon and improves diet quality (and hence suming that production and productivity animal productivity). Improving breeds and 624 P. Ericksen, P. Thornton and G. Nelson grain supplementation had the lowest mitiga- The special issue of Proceedings of the Na- tion potentials. The total of all interventions tional Academy of Sciences USA used the first combined was a range of 6–12% reduction in biologically consistent, spatially disaggregated current livestock-related emissions (depending global data set of the main biophysical inter- on assumptions about adoption rates). actions among feed use, animal production and Herrero et  al. (2016) assessed three inter- GHG emissions. It highlighted three points: (i) ventions: (i) technical and management inter- feed-use efficiencies are a key driver of productiv- ventions; (ii) intensification and the associated ity and therefore of GHG emissions per unit of structural changes of livestock systems; and output; (ii) grasslands are a critical resource, (iii) moderation of demand for livestock products. which provide almost 50% of plant biomass for All such interventions have the technical poten- animals; and (iii) mixed crop–livestock systems tial to mitigate emissions from livestock, but produce over 60% of animal production across their economic potential may be far smaller due the world. to adoption costs on the supply side and a lack of CH 4 from enteric fermentation is the largest effective policies for promoting healthy levels of source of non-CO2 emissions, with cattle ac- consumption of livestock products (Fig. 16.4). counting for 77%. Developing world regions In 2013, a special issue of Proceedings of contribute 75% of the global emissions from the National Academy of Sciences USA was pub- livestock, and sub-Saharan Africa is a global lished, representing several years of intensive hotspot for high emissions intensities, driven by work to improve the modelling of heterogeneity low animal productivity per unit of land and in livestock system characteristics and their low-quality feeds, which extend the growing evolution, using spatially explicit data sets and periods of animals raised on grasslands or crop different assumptions by region about future residues. growth. Herrero et al. (2013) focused on differ- Herrero et  al. (2016) updated the 2013 ences among systems in land-use intensities analysis with new data on livestock production and GHG emissions. They concluded that these systems and on differences between technical differences showed potential for improvements mitigation potential and economic potential. in all tropical livestock systems, given their low First, they reviewed the major studies of GHG productivity. This study produced an innovative emissions from livestock, including both IPCC data set on biomass use, production, feed effi- emissions guidelines as well as life cycle assess- ciency, excretion and GHG emissions for 28 re- ments, focusing on uncertainties in the esti- gions, eight livestock production systems, four mates. They estimated that over the period animal species and three livestock products 1995–2005, annual global GHG direct and (Figs. 16.5–16.7). indirect emissions from livestock were 5.6–7.5 0.8 0.7 0.6 0.5 0.4 0.4 0.2 0.1 0 Carbon sequestration Improved feed Use of feed Avoided LUC due Animal Rangeland Carbon sequestration Manure due to improved digestibility additives to intensification management rehabilitation due to legume sowing management grazing management of ruminant systems Fig. 16.4. Mitigation potentials of supply-side measures. Red represents the range for each practice, where available. LUC, land-use change. (From Herrero et al., 2016.) Technical mitigation potential (GtCO2eq) Ruminant Livestock and Climate Change in the Tropics 625 (a) Bovine milk (b) Bovine meat EUR EUR OCE LGA OCE NAM LGH NAM LAM LGT LAM EAS MXA EAS SEA MXH SEA SAS MXTUrban SAS MNA Other MNA SSA SSA 0 50 100 150 200 250 0 5 10 15 Million t Million t (c) Small ruminant milk (d) Small ruminant meat EUR EUR OCE OCE NAM NAM LAM LAM EAS EAS SEA SEA SAS SAS MNA MNA SSA SSA 0 1 2 3 4 5 6 7 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Million t Million t Fig. 16.5. Bovine meat (a) and milk (b) production and small ruminant milk (c) and meat (d) by region. EUR, Europe; OCE, Oceania; NAM, North America; LAM, Latin America and the Caribbean; EAS, Eastern Asia; SEA, South-East Asia; SAS, South Asia; MNA, Middle East and North Africa; SSA, sub-Saharan Africa; LGA, livestock/grazing/arid; LGH, livestock/grazing/humid; LGT, livestock/grazing/ temperate; MXA, mixed/arid; MXH, mixed/humid; MXT, mixed/temperate; Other, other systems; Urban, urban systems. (From Herrero et al., 2013.) GtCO2eq. They then estimated emissions reduc- be 175, 200 and 225 tCO2eq. For measures tar- tions potential for several supply options, con- geting soil carbon sequestration in grazing cluding that these practices could help mitigate lands, higher mitigation levels of 250, 375 and between 0.01 and 0.5  GtCO2eq/year or about 750 tCO2eq/year were found. two-thirds of livestock emissions. The supply Most emissions results to date have been options included feed additives, improved feed derived from studies of temperate livestock and digestibility, manure management, soil carbon extrapolated to the tropics. Without more accur- sequestration in grasslands, animal productivity ate data, existing models used to calculate emis- and health, and avoided deforestation due to sions from smallholdings are more likely to give intensification unreliable estimates and, in turn, are less useful Demand-side options, discussed in greater for policy in the tropics (Rufino et al., 2014; Kim detail below, comprise a new agenda that has and Kirschbaum, 2015). In 2013, ILRI began gained traction in Europe and North America in collaboration with the Karlsruhe Institute of response to concerns that livestock production Technology in Germany to measure the global uses a disproportionate amount of land, emits environmental impacts of livestock production, significant GHGs and can have negative health in particular GHG emissions, in order to derive effects. The study assessed the potential for miti- better estimates under tropical conditions gation over the range of GHG taxes of US$20, (e.g. Zhou et  al., 2014a, near Lake Victoria; US$50 and US$100/tCO eq. The 2030 mitiga- Zhou et al., 2014b, for a wheat–maize rotation 2 tion potentials for these taxes were projected to in subtropical China; Pelster et  al., 2017, for 626 P. Ericksen, P. Thornton and G. Nelson (a) Grains (b) Grass EUR EUR OCE OCE NAM NAM LAM LAM EAS EAS SEA SEA SAS SAS MNA MNA SSA SSA 0 100 200 300 400 0 100 200 300 400 500 Million t Million t (c) Occasional feeds (d) Stover Dairy cattle EUR EUR Dairy small ruminant OCE OCE Other cattle NAM NAM Other small ruminant LAM LAM Pigs EAS EAS Poultry SEA SEA SAS SAS MNA MNA SSA SSA 0 50 100 150 200 0 50 100 150 200 250 300 Million t Million t Fig. 16.6. Regional estimates of feed production for grains (a), grass (b), occasional feeds (c) and stover (d). See Fig. 16.5 for abbreviations. (From Herrero et al., 2013.) c attle and tree fodder in Kenya; Rosenstock et al., The Mazingira facility responds to several 2016, for croplands in Kenya and Tanzania). analytical challenges. Little is known about cur- In 2012, ILRI researchers engaged with the rent baselines (e.g. Hickman et al., 2014 found CGIAR Research Programme on Climate Change, only 20 studies on N2O and NO fluxes from agri- Agriculture and Food Security (CCAFS) flagship culture in sub-Saharan Africa). Second, existing on Low Emissions Agriculture began collaborat- models have not accounted for all of the processes ing on SAMPLES. Rosenstock et  al. (2013) de- through which livestock emit GHGs (Rufino et al., scribed the SAMPLES protocol for improving data 2014). Third, time is needed for measurements quality and quantity from tropical smallholdings. to start and for data quality to be evaluated. An This protocol was based on five innovations: (i) initial SAMPLES study provided ‘the most com- systematic data collection; (ii) informed sampling prehensive study in Africa to date’ of annual from emissions hotspots; (iii) quantifying emis- in situ CO 2, CH4 and N2O emissions from soils in a sions at several spatial scales, including whole mixed crop–livestock system in western Kenya farm and landscape; (iv) using a multi-criteria ap- (Pelster et  al., 2017). The authors found that proach to link GHG emissions reductions with land classes did not make much difference in productivity gains; and (v) offering cost-differen- fluxes, nor did management because input use tiated measurements, depending on user needs. was so low. The lack of a management effect is ILRI established a modern environmental probably representative of most smallholdings laboratory in 2014. The Mazingira (Kiswahili in Africa, but the land class effect has not been for environment) Centre is the only facility in widely tested. A second study found that land Africa with the capacity for accurate measure- use and soil texture influenced GHG fluxes, al- ments of GHG emissions from soils, manure and though this study measured fluxes in the labora- ruminant digestion, using field and laboratory tory rather than in situ (Wanyama et al., 2018). measurements and analysis (https://mazingira. Pelster et  al. (2016) measured emissions from ilri.org; accessed 8 March 2020). excreta from cattle fed diets representative of Ruminant Livestock and Climate Change in the Tropics 627 (a) Ruminant GHG emissions (b) EUR LGA LGH OCE LGT MXA NAM MXHMXT LAM URBANOTHER EAS SEA SAS MNA SSA kg CO2eq/kg protein 10 25 50 1002505001000 0 100 200 300 400 500 Mt CO eq 2 (c) (d) Milk Meat 10000 10000 5000 LGA EUR 5000 LGH OCE LGT NAM MRA LAM MRH EAS 1000 MRT SEA 1000 SAS 500 MNA 500 SSA 100 100 50 50 10 10 8 9 10 11 12 8 9 10 11 12 ME (MJ/kg DM feed) ME (MJ/kg DM feed) Fig. 16.7. Global non-CO2 GHG emissions from ruminant livestock. (a) Non-CO2 GHG emissions from global ruminant livestock (cattle, sheep, and goats) by production system and region. (b) Spatial distribution of non-CO2 GHG emissions from ruminants (kg CO2eq/kg edible animal protein). (c, d) Relationship between diet quality of ruminants and the non-CO2 GHG emission intensity for edible animal protein from ruminant milk (c) and meat (d). DM, dry matter; see Fig. 16.5 for other abbreviations. (From Herrero et al., 2013.) East African conditions and found that CH4 and variation in live weight, feed sources and feed N2O emissions were lower than current IPCC es- availability. timates. The lower emissions were apparently Previous studies have shown that improv- due to the low nitrogen content of the excreta, ing dietary quality and quantity results in live reflecting the low nitrogen content of animal weight gains, which reduce emissions intensities diets in the sample. per unit of live weight. Feed quality is the key Another problem in establishing tropical factor influencing CH4 production from rumin- emissions baselines is seasonal variability in feed ant digestion as shown in a meta-analysis of ani- quality and supply. Goopy et al. (2018) defined a mal experimentation data (Hristov et al., 2013)1. method based on animal energy requirements, Blümmel et al. (2009, 2013) studied the poten- derived from field measurements of live weight, tial to reduce GHG emissions in India. Although milk production, locomotion and feed digestibil- the research emphasis was on use of crop res- ity. Emissions factors for annual CH 4 production idues to improve productivity, the India work were produced for three locations in western found that a collateral benefit could be reduc- Kenya (Ndung’u et al., 2018; Onyango, 2018). tions in GHG emissions intensities per unit of In all locations, the emissions factors per unit of output, and possibly a reduction in total emis- live weight by type of animal and agroecology sions per herd, if productivity gains allowed a re- differed from the current IPCC estimates due to duction in herd sizes. kg CO2eq/kg protein kg CO2eq/kg protein 628 P. Ericksen, P. Thornton and G. Nelson Demand-side options ‘total abatement calorie cost’ – than policies tar- geting emissions from livestock only. Much has recently been written about de- Revell (2015) used a partial equilibrium mand-side interventions (Garnett 2009; Smith model of beef, poultry, pig and sheep meats for et  al., 2013; Valin et  al., 2013). Springmann the major regions of the world to explore scen- et al. (2017) estimated the mitigation benefits of arios that might reduce meat consumption and a tax on foods whose production is GHG inten- GHG emissions. He concluded that economic sive and where current consumption levels in and population growth to 2050 without any some countries have negative health effects mitigation measures would lead to a 21% in- (Fig. 16.8). They found a double benefit from crease in per capita meat consumption and a this policy approach – a substantial reduction in 63% increase in total consumption and GHG GHG emissions, and health-promoting out- emissions by 2050. However, the mitigation pro- comes in middle- and high-income countries. jections from the scenarios generated only a Average GHG taxes on food commodities (based 14% reduction in cumulative emissions from the on an emissions tax of US$52/tCO eq) were baseline 2050 projections, insufficient to meet 2 highest for animal-sourced foods, such as beef the 2050 target of a 50% reduction in global (US$2.8/kg), lamb (US$1.3/kg), and pork and GHG emissions. poultry (US$0.3/kg each), which corresponded Schader et al. (2015) explored the scope for to 40%, 15%, 7% and 9% of the mean global sustainable livestock production by modelling producer prices of these commodities. the effects of a third strategy in which animal Springmann et  al. (2018) showed that be- feeds that compete with food production are re- tween 2010 and 2050, as a result of expected duced, and in an extreme scenario, animals are changes in population and income levels, the fed only from grasslands and by-products from environmental effects of the food system could food production. While the extreme scenario increase by 50–90% in the absence of techno- largely reduces animal protein per capita by logical changes and dedicated mitigation meas- some 70%, it could provide adequate energy ures. The same study also found that no single and proteins and reduce environmental impacts measure is enough to keep these effects within compared with a 2050 reference scenario as all planetary boundaries simultaneously, and f ollows: GHG emissions −18%, arable land oc- that a combination of measures is needed to cupation −26%, nitrogen surplus −46%, phos- sufficiently mitigate the projected increase in phorus surplus −40%, non-renewable energy e nvironmental pressures. use −36%, pesticide-use −22%, and freshwater Havlik et al. (2014) found that sustainable use −21%. intensification of livestock production systems White and Hall (2017) used the total re- might become a key climate-mitigation tech- moval of animals as the extreme boundary to nology. However, livestock production systems potential mitigation options and required the vary widely, making the implementation of cli- fewest assumptions to model the yearly nutri- mate-mitigation policies a costly challenge. They tional and GHG impacts of eliminating ani- projected that by 2030 autonomous transitions mals from US agriculture. Although modelled towards more efficient systems would de- plants-only agriculture produced 23% more crease emissions by 0.74 GtCO 2eq/year, mainly food, it met fewer of the US population's require- through avoided emissions from the conversion of ments for essential nutrients. When nutritional 162 million ha of natural land. A moderate miti- adequacy was evaluated by using least-cost diets gation policy targeting emissions from both the produced from the foods available, more nutri- agricultural and land-use change sectors with a ent deficiencies, a greater excess of energy and a carbon price of US$10/tCO2eq could lead to an need to consume a greater amount of food solids abatement of 3.22 GtCO2eq/year. Livestock sys- were encountered in plants-only diets. In the tem transitions would contribute 21% of the simulated system with no animals, estimated total abatement, intra- and interregional reloca- agricultural GHG decreased (28%) but did not tion of livestock production another 40% and all fully counterbalance the animal contribution of other mechanisms would add 39%. Mitigation GHG (49% in this model). This assessment sug- policies targeting emissions from land-use change gests that removing animals from US agriculture are five to ten times more efficient – measured in would reduce agricultural GHG emissions but Ruminant Livestock and Climate Change in the Tropics 629 (a) 12 (b) 45 (c) Price GHG tax Price Consumption 10 35 0.0 8 25 –0.2 6 15 Beef Milk 4 5 –0.4 Oils Lamb 2 –5 Rice –0.6 Poultry 0 –15 Pork Wheat –0.8 Vegetables Eggs Other –1.0 Fig. 16.8. Impacts of GHG taxes on food prices, consumption and GHG emissions. (a) Prices and GHG taxes by food commodity. (b) Percentage changes in price and consumption by food commodity. (c) Change in GHG emissions by food commodity and region. Regions include high-income countries (HICs) and the low- and middle-income countries of Africa (AFR), the USA (AMR),the Eastern Mediterranean (EMR), Europe (EUR), South-east Asia (SEA) and the Western Pacific (WPR), and an aggregate of all regions (World). Impacts are for a tax scenario in which GHG taxes are levied on all food commodities. (From Springmann et al., 2018.) P r i c e ( U S $ / k g ) L a m b B e e f P o r k P o u l t r y F r u i t s ( t e m p . ) L e g u m e s V e g e t a b l e s F r u i t s ( t r o p . ) R i c e O i l s M i l k O i l c r o p s S u g a r R o o t s W h e a t O t h e r g r a i n s M a i z e C h a n g e ( % ) B e e f O i l s M i l k L a m b P o u l t r y O t h e r g r a i n s R i c e W h e a t P o r k M a i z e E g g s O i l c r o p s V e g e t a b l e s S u g a r L e g u m e s R o o t s F r u i t s ( t r o p . ) F r u i t s ( t e m p . ) C h a n g e i n G H G e m i s s i o n s ( G t C O e q ) 2 W o r l d H I C A F R A M R E M R E U R S E A W P R 630 P. Ericksen, P. Thornton and G. Nelson would also create a food supply incapable of from animal production and animal product supporting the US population’s nutritional re- consumption; and (vii) extend field tests under quirements. tropical conditions of actual emission levels and possible reductions. Examples of the latter are pilot projects for Low Emissions Development The Future options (Ericksen and Crane, 2018; Kashangaki and Ericksen 2018). Future climate research priorities for tropical There has been less research on climate livestock have three components – mitigation, adaptation in tropical livestock than there has adaptation and policy. been on mitigation. Additional adaptation Research has established the mitigation research requires a broader view of adaptation potential of technical changes in the systems beyond technical change, involving changes in responsible for most GHG emissions from pro- behaviour, institutions and culture. Priorities for duction animals. The best-understood systems adaptation studies in tropical livestock systems are dairy and beef, which account for about include the following: 70% of GHG emissions from world livestock supply chains (Gerber et  al., 2013, p. 18). • More effort on the specific tropical problems Other work by Gerber et  al. (2011), on inten- of heat stress and animal performance, on sive dairying in a temperate climate, has estab- the genetics of reproduction under greater lished ranges of possible mitigation gains and heat stress, and on pests and diseases that the components – feed, genetics, health and do not exist in temperate climates. management – of such gains and the output • Improved capacity for surveillance of climate- costs of those changes. The lessons of this sensitive diseases, coupled with new diag- work are applicable as first approximations to nostics for these diseases (see Chapters 2, 3 mitigation paths for low-productivity dairying and 5–10, this volume). in the tropics, but more in situ measurements • An expanded programme of characteriz- from tropical systems are needed to sharpen ing, testing and disseminating perennial estimates of potential gains. Mitigation work forage species adapted to hotter, drier and on the supply side must rely less on the as- more variable climates (see Chapters 12 sumption that temperate data and models are and 13, this volume). directly transferable to tropical conditions and • Decision support tools to target adaptation instead will require greater focus on new find- programmes and to monitor their effects, ings under tropical conditions. including new measures of adaptation at The future of mitigation research is to: the household level. (i) estimate potential GHG reductions from less The models underpinning policy recom- well-studied tropical systems, such as extensive mendations for climate are inherently complex beef on pastures, intensive fattening on small- because of the number and scale of the climate, holdings and nutrient cycling in mixed crop– biological and behavioural relationships in- livestock farms; (ii) identify the components – feed volved. Policy recommendations from climate re- quality and management, animal genetics, health, search involving animals, in particular, require a overall herd management, and demand reduc- closer integration of supply- and demand- side tion – of potential GHG reductions; (iii) refine modelling because of the interactions between estimates of success probabilities from investiga- the two sides: tions of feed-use efficiency in the tropics; (iv) iden- tify profitability constraints, including policies, to • More research is needed on the policy in- adoption of potential technical changes; (v) ‘back- centives to promote broad adoption of cast’ projections from published models, not- mitigation and adaptation practices in the ably MarkSim and LGP-based work, into actual tropics, given the externality problems in- data to test the validity of these projections; volved in both. (vi) strengthen demand-side mitigation research • The literature comparing supply and de- in comparison with supply-side efforts to esti- mand measures is limited. Future modelling mate least-cost paths for emissions reductions by ILRI and partners must involve closer Ruminant Livestock and Climate Change in the Tropics 631 integration between supply and demand a ssistance to such risk-management components (e.g. Weindl et al., 2017). interventions as IBLI. • The dependence of arid rangelands on • In mixed crop–livestock systems, we also livestock demands an extended research have not assessed the impacts of production and policy effort that recognizes that shifts away from ruminants towards poultry technical options are limited (Ericksen on livelihoods and food security. et  al., 2012; Herrero et  al., 2016) for • Countries also need support to develop GHG mitigation, for adaptation and for protocols and data to monitor and report on raising productivity even (see Chapter their commitments to UNFCCC and to pre- 11, this volume, on the difficulties of pare credible investment plans. raising productivity from arid range- lands). 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