Unearthing the data behind the most prevalent livestock facts
On June 8 2018 LD4D hosted an online discussion to launch a set of factsheets and discuss the provenance of popular livestock facts, recognise gaps in knowledge, and get up to speed on the latest figures. Watch the recorded webinar and read a summary of the discussion below.
Watch the recorded webinar
We welcome further questions and comments, please leave them at the end of this page.
Why check the facts?
Livestock is often at the centre of economic, social and environmental discussions, but popular facts are not always rooted in reliable data.
That’s why we’re digging into the evidence behind commonly cited livestock facts and figures to better understand their origins, calculations and context. This webinar will launch a new series of factsheets investigating the most widespread claims. What we’ve found may surprise you!
Facts checked (so far):
- Livestock and livelihoods: Do livestock support the livelihoods of around one billion poor people globally?
- Livestock and economy: Does the livestock sector make up 40% of total agricultural GDP globally?
- Livestock and zoonotic disease: Of emerged human disease epidemics, have 75% really been of animal origin? And overall, are 60% of human pathogens of animal origin?
- Livestock disease eradication: Did global eradication of Rinderpest bring billions of dollars of benefits
During the webinar, a panel of experts shared their perspectives and ideas for the way forward.
|Professor Andy Peters, Director (Supporting Evidence Based Innovations, University of Edinburgh)|
|Gareth Salmon, Researcher (Supporting Evidence Based Innovations, University of Edinburgh)|
|Gilbert Nakweya, Journalist (SciDev.net Sub-Saharan Africa)|
|Shirley Tarawali, Assistant Director General (International Livestock Research Institute – ILRI)|
Here is a summary of the lively discussion between the online audience and panelists. There was not enough time to address all the comments and questions during the webinar, but the panelists and Livestock Fact Check working group have responded to these below.
Comment: When it comes to “valuing livestock” you should also consider how camels offer insurance against climate unreliability
Reply: This a very good point. Camels and other livestock are a valuable resource when environmental conditions are challenging. For instance in communities in dry regions where crops are impractical (Thornton and Gerber, 2010, Thornton, 2010, Turner et al., 2014). The challenge we raise with our GDP fact check, is that GDP is unlikely to capture these ‘values’ of livestock.
Question: Should we recalculate the livestock facts?
Reply: This is an interesting question. To answer it several questions need to be asked for each individual fact:
- Is there a tangible benefit or specific reason for a recalculation? (Will a recalculation provide anything more to the fact’s purpose?
- Is it the best application of resources to recalculate, or there other priorities? (As Shirley Tarawali mentioned in the webinar, although we don’t know the true global benefit of Rinderpest eradication, we do have case studies demonstrating benefits outweighing costs therefore are resources better placed focusing attention on other livestock diseases)
- Do we have the quantity and quality of data to attempt improved recalculations?
The Livestock Data for Decisions community of practice, with its diversity of members, is well placed to provide answers to these questions. There is also enthusiasm with LD4D to improve data and method sharing and harmonisation; which could improve our ability to improve facts.
Question: There is a lot of controversy around the contribution of livestock to GHG emissions. Is there a plan to develop a fact sheet on this? Can you do justice to the complexities in a fact sheet?
Reply: Yes, Livestock and Greenhouse Gas emissions is one of the Fact Check sheets we are currently working on. We are looking to illustrate the significant variation in emissions intensity (volume of GHG emissions per kg of livestock product) for livestock production systems both within defined production systems and between different defined production systems. This variation is often lost when single figures are quoted for the impact of livestock on the environment. We will also discuss the influence of livestock multi-functionality (common in LMICs) on the emissions intensity values. Values tend to drop if you include all benefits of livestock, not only protein production (see work by Weiler, Udo, and colleagues (2014)).
Question: What change(s) would you like to see come out of this project?
Reply: This project has an objective to promote the appropriate interpretation of information (facts) when informing discussions and decisions. We do this by illustrating the provenance of several popular facts; through this process for some specific examples, we raise awareness of the risks of misinterpretation when details such as methods and context are lost. With such increased awareness, we envisage that when facts are used, users will be responsible in investigating specific provenance, and assessing fitness-for-purpose, as part of their process. The project will also highlight areas where we, as a community, require more knowledge, promoting further research and data collection.
Comment: I agree with ILRI that tipping points (thresholds) are important for determining when data is ‘good enough’ for a particular advocacy purpose. Also from the point of view of determining thresholds for making interventions e.g. onset of Rift Valley Fever epidemics
Reply: This is true, thresholds are important for informing policy makers when to take action. However, we need accurate data and confidence in our ‘facts’ to know when we have reached thresholds or to have insight into trends that may be occurring. There are examples, for instance the number of poor livestock keepers, where there does not appear to be enough information to suggest a trend over time.
Comment: The gap minder tool is great for presenting figures that capture variations
Reply: Thanks, we also recently came across gapminder.org and agree it has great potential for visualising data variations. As part of LD4D we also have a data visualisations working group, who are considering how we can use effective visualisations (including dashboards) to demonstrate livestock forecasting (populations, diseases etc.).
Question: How about ‘best guesses’? The lack of historic or contemporary data suggests that the fact themselves might be somewhat shaky. Hence, maybe they are ‘best guesses’. It is a problem shared across various domains working in low and middle income countries (LMICs) on vulnerable populations.
Replies: We recognise that data, particularly in LMICS, often requires improved accuracy. In addition, some information on aspects of livestock systems is rarely comprehensively gathered. Therefore, in the majority of cases ‘facts’ will be best estimates. This is where livestock modelling has a role to play in filling in the gaps of information we don’t know. Expert opinion also has a key role to play here in sense checking results and both data collection and modelling exercises. As Professor Andrew Peters mentioned in the webinar, SEBI (Supporting Evidence Based Interventions) has recently made use of expert opinion to validate data samples from Ethiopia. The LD4D community offers a great opportunity to access such experts and help improve/guide our confidence in data.
Question: How can International organisations involved in the collection of data contribute to a better use and understanding of the information collected and shared with the global community?
Reply: The LD4D community of practice offers a unique forum for international organisations to collaborate, sharing methods and information. Such collaboration will put us all (those of the livestock research and development community) in a better place to apply appropriate data to answer questions and to communicate clear, well informed, messages to the global community. We strongly believe in the need for such collaboration and better communication between key stakeholders. Within LD4D are several working groups and sub-projects dealing with developing knowledge platforms and data portals, data visualisations, data quality, app development, livestock modelling and more. Learn more about our working groups and their activities.
Question: How can scientists and journalists work together on these issues in Africa? Is tracing an important point?
Reply from Gilbert Nakweya (SciDev.net Journalist): Here is how journalists try to ensure accuracy:
- Sourcing media heavily relies on livestock researchers, scientists, policy makers, research institutions for facts.
- Multiple sourcing is encouraged to increase certainty on livestock facts.
- If FAO says 40% of agricultural GDP globally is contributed by the livestock sector; what does AfDB, World Bank, ILRI, Ministry of Agriculture, NARs, say on the same
- Questioning and digging deep into facts looking out especially for uncertainties.
Question: Sharing data is not always happening when a scientific paper is published. Perhaps we should put lot more emphasis on the “open access” approach.
Reply: There are obviously many benefits of open access data attached to publications, for instance transparency. Many international organisations already have open access data policies. In addition the LD4D community of practice is encouraging the sharing of data, or information about where to find data, and this should improve the situation for the wider community.
Question: Does the panel think it is worth reaching out across disciplines and taking a transdisciplinary approach that includes ‘citizen science’ to collect more data?\
Reply: Shirley Tarawali replied to this question during the webinar encouraging us to look beyond empirical science data. There is useful information in other sources (for instance social studies). There are also opportunities to bridge gaps between different disciplines through these fact checks. For instance a livestock production and human nutrition factsheet could link the livestock community with human health specialists/nutritionists.
Livestock also appear to be increasingly present on broader data collection projects, such as the World Bank Group Living Standards Measurement Study (LSMS) surveys. As a community we need to encourage this recognition of the significance of livestock in LMICs.
Question: How should the research community improve estimations of the impact/ benefit of eradicating diseases? Not only to the global economy but individual livestock rearing communities? Including cultural, traction, etc. values.
Reply: This is a tough question as it is not easy to quantify the value (and therefore impact/benefit) of non-marketable livestock outputs. There are examples of studies which have taken on the challenge of quantifying various livestock values in LMICs, and have demonstrated significant increases in total value (Behnke, 2010, IGAD, 2013).
With regards to the impact of livestock disease at a global scale, there is a new initiative led by Jonathon Rushton at University of Liverpool looking to address this question in detail.
Question: Any specific focus on bridging the gap between data and presentation thereof, and data for decision-making?
Reply: LD4D has another working group ‘data visualisations’ which is looking to address how data should be made accessible to inform decisions.
Livestock Fact Check is an ongoing project which investigates and clarifies commonly cited facts about livestock. The livestock factsheets and webinar are produced by the Livestock Data for Decisions (LD4D) community of practice. LD4D aims to drive informed livestock decision-making through better use of existing data and analyses. Learn more at ld4d.org.
Photo credit: Z. Sewunet (ILRI)