ILRI news

Collecting milk in Kenya’s informal market (photo credit: ILRI/Dave Elsworth).

Do estimates of the agricultural gross domestic product (GDP) of African nations really underestimate the value of the contribution from the livestock sector, as livestock specialists at the International Livestock Research Institute (ILRI) and elsewhere frequently complain? In Kenya and Ethiopia, the answer is a resounding ‘Yes’.

A new study by the Inter-Governmental Authority on Development (IGAD) Livestock Policy Initiative (LPI), which worked with national partners, concludes that livestock’s contribution to Kenya’s agricultural GDP is a whopping two and a half times larger than the official estimate for 2009. An earlier IGAD study concluded that livestock’s contribution to Ethiopia’s agricultural GDP has been even more dramatically under-reported; livestock’s contribution is now being estimated at three and a half times larger than that of the last official estimate available.

In Kenya, ‘This increase of 150% over official estimates means that the livestock contribution to agricultural GDP is only slightly less than that from arable agriculture, i.e. 320 billion Kenyan shillings for livestock (about $4.21 billion US dollars in 2009) versus 399 billion Kenyan shillings for crops and horticulture (in 2009 roughly $5.25 billion US dollars). . . .

‘According to the revised estimates, milk is Kenya’s most economically important livestock product, providing a little less than three quarters of the total gross value of livestock’s contribution to the agricultural sector. In terms of its contribution to agricultural GDP, milk is about four times more important than meat.

‘Cattle are Kenya’s most important source of red meat, supplying by value about 80% of the nation’s ruminant offtake for slaughter. More than 80% of the beef consumed in Kenya is produced by pastoralists, either domestically or in neighbouring countries and then imported on the hoof, often unofficially.’

In addition, the broad range of benefits rural food producers derive from livestock keeping—including manure for fertilizing crop field, traction for pulling ploughs, and serving as a means of savings and credit and insurance—represent about 11% of the value of the livestock contribution to GDP in Kenya and more than 50% in Ethiopia.

‘The conclusion to be drawn from this study is that Kenya’s livestock are economically much more important than hitherto believed; in fact, only marginally less than crops and horticulture combined. Agriculture and forestry are by far Kenya’s most important economic sector in terms of domestic production and it would now appear that livestock provide about 43% of the output from this sector. . . .’

We link here to the whole policy brief from the Inter-Governmental Authority on Development (IGAD) Livestock Policy Initiative (LPI – IGAD LPI website). The brief was based on working paper by the United Nations Food and Agriculture Organization and IGAD: The Contribution of Livestock to the Kenyan Economy, No. 03-2011, by Roy Behnke and David Muthami.

Read Part 1 and Part 2 of the earlier IGAD LPI working papers on Ethiopia (also a policy brief).

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The Commission on Sustainable Agriculture and Climate Change, an initiative of the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), is identifying policy changes and actions needed to help the world achieve food security in the face of climate change; the Commission launched this summary for policymakers on 16 Nov 2011 (photo on cover by Neil Palmer/CIAT).

The current issue of New Scientist publishes an article describing a recently released study, ‘Achieving Food Security in the Face of Climate Change’, which was commissioned by the CGIAR Research Program on Climate Change, Agriculture and Food Security (Consultative Group on International Agricultural Research). For more on that study, see the CCAFS news release of 16 November 2011: ‘Global Commission Charts Pathway for Achieving Food Security in Face of Climate Change‘.

Sujata Gupta’s New Scientist article on meat consumption, ‘Just how much meat can eco-citizens eat?’ (online publication date: 16 November 2011; print issue date: 19 November 2011; print issue number: 2839), contains what we believe is a factual error. Gupta quotes a 2007 article in the Lancet (‘Food, livestock production, energy, climate change, and health’, doi:10.1016/S0140-6736(07)61256-2) that 80% of agricultural greenhouse gas emissions come from meat production.

More credible figures, compiled from international global assessments by agricultural systems analyst Mario Herrero and his colleagues at the International Livestock Research Institute, are the following.

The total agricultural sector emits around 25–32% of global anthropogenic greenhouse gas emissions. Crops emit 14% (EPA 2006) and all livestock emit 11–18%, depending on how emissions are attributed (FAO 2006, EPA 2006, PBL 2010). The emissions from livestock can be divided roughly as 30% methane from enteric fermentation, 30% nitrous oxide from manure management and 40% from carbon dioxide from land-use changes for grazing and feed production (FAO 2006). Figures for the emissions from land-use changes carry a lot of uncertainty. Emissions can also be divided by species and product. For example, the dairy sector is responsible for roughly 27% of greenhouse gas emissions from livestock (FAO 2010) while monogastric production (pigs/poultry) is responsible for  10–20% of the livestock emissions. Hence, it is not possible that beef production can account for 80% of all agricultural emissions. Even if beef cattle represent 50–60% of livestock emissions, this translates roughly into a figure close to 30–35% of all agricultural emissions—certainly not 80%. What is true is that of all livestock products, beef is the most inefficient in terms of greenhouse gas emissions produced per unit of product, especially compared to dairy and monogastrics (De Vries and de Boer 2010).

Herrero and his colleagues at ILRI, CCAFS and elsewhere are publishing updates on topics concerning livestock production and climate and other kinds of global change. Look out, for example, for the following book chapter, due next month, which we will report on in this blog: M Herrero, PK Thornton, P Havlík, and M Rufino, Livestock and greenhouse gas emissions: Mitigation options and trade-offs. In: E Wollenberg, A Nihart, ML Tapio-Bistrom and C Seeberg-Elverfeldt (eds), Climate Change Mitigation and Agriculture, Earthscan, London, UK (in press).

See an earlier report on a similar topic in this ILRI News Blog: Livestock and climate change: Towards credible figures, 27 Jun 2011.

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The Animal Genetics Training Resource (AGTR) is a unique, ‘one stop’, user-friendly, interactive, multimedia resource, targeted at researchers and scientists teaching and carrying out research in animal biodiversity and genetics.

It is a dynamic training resource designed to help inform the design and implementation of breeding programmes and provide information that will empower countries and institutions to undertake their own research. It covers established and rapidly developing areas, such as genetic based technologies and their application in livestock breeding programmes.

Core modules in the AGTR are:

1. Global perspectives on animal genetic resources for sustainable agriculture and food production;
2. Improving our knowledge of tropical indigenous animal genetic resources;
3. Sustainable breeding programmes for tropical farming systems;
4. Quantitative methods to improve the understanding and use of animal genetic resources; and
5. Teaching methods and science communication.

The modules are supported by over 40 case studies that summarize real-life experiences and capture indigenous knowledge and lessons learnt from developing countries. The case studies also illustrate principles and methodologies commonly applied in animal genetics, from real-life situations and they highlight knowledge gaps appropriate for post-graduate theses or further research.

A linked breed information tool incorporates all the breeds highlighted in the modules/case studies. Practical examples, exercises, compendia, a library with full-text articles, and links to relevant web resources are included. It also has links to many other information sources on and related to AnGR, including the Domestic Animal Genetic Resources Information System (DAGRIS: http://dagris.ilri.cgiar.org) and the Domestic Animal Diversity Information System (DAD–IS: http://dad.fao.org). A high quality and accuracy of the contents of the AGTR is assured through an external review process by subject matter specialists.

View the Resource online at http://agtr.ilri.cgiar.org

AGTR is a joint product of ILRI and SLU – the Swedish University of Agricultural Sciences (www.slu.se)

The first version of AGTR was released as a CD in October 2003. It included the first versions of the five training modules, case studies and breed information focused on livestock breeds mainly in Africa and to a small extent in Asia. It also included a few exercises, two video clips and a library of 50 documents.

The second version, released in 2006, was more expansive and comprehensive than Version 1. It was made available both as a CD and on the Web, and included additional information for Asia as well as for Africa.
Version 3 is online in November 2011 on a fully web-enabled platform, which allows for direct online revisions and content comments by authors. CD versions of the same will be prepared in 2012. Significant changes have been made to the content of the Modules. All of the case studies were externally reviewed and subsequently revised, and new case studies have been added. Software manuals for word processing and presentation have been updated, and an example of using the statistical software ‘R’ (freely available) has been added. The greatly enhanced multimedia section now includes links to film and clips by ILRI, as well as pictures of numerous livestock breeds.

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Students and teachers of biometrics and applied statistics in agriculture and livestock have long faced a shortage of case studies and datasets suited to African settings.

Version 2 of the Biometrics and Research Methods Teaching Resource provides 17 case studies (each with its own Excel data sets) prepared by students, lecturers and researchers at the University of Nairobi, University of Swaziland, University of Kwazulu-Natal, Islamic University of Uganda and ILRI).

Each case study follows the typical stages in a research process:

1. Research strategy (deciding research objectives; choosing the type of study)
2. Study design (planning the study; accounting for variation; sampling; designing an experiment; designing a survey).
3. Data management (collecting data; organising data; storing data)
4. Data exploration (looking at data; describing data; formulating statistical models).
5. Data analysis (modelling data; handling variation; applying different statistical techniques – analysis of variance, regression analysis, general linear models).
6. Reporting (interpreting and presenting results; communicating research results).

Six teaching modules complement the cases and provide additional teaching and learning material of a practical nature.
In this second version, users can be linked directly to subjects of interest. The presentation and description of data sets has improved and GenStat dialog boxes now appear within the case studies. The Teaching Resource relies on the statistical package GenStat (two case studies also demonstrate the use of R), which can readily be downloaded with a ’Discovery’ version free for not-for-profit users in sub-Saharan Africa.

To make the resource more usable by teachers and students, this version will include both a zipped website version for those with intermittent internet connections so they can download the CD and separate pdf documents.

View the Teaching Resource online at http://www.ilri.org/biometrics

A CD version of the Resource is available on request from ILRI (contact a.m.odanga@cgiar.org)

The Teaching resource was funded by the Ford and Rockefeller Foundations.

View an interview with John Rowlands on the resource:

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