This years Climate Smart Agriculture (CSA) Conference 2017 took place from 27th-30th November 2017 in Johannesburg, South Africa. The conference brought policy makers, NGOs and scientists together to discuss the progress being made in implementing CSA primarily in developing countries. Each day was organized around plenary sessions and followed by parallel focused sessions in the afternoon. The Mazingira Centre team not only contributed by presenting the first results on the greenhouse gas emissions work currently carried out in Kenya but also chaired session 7.1 “Climate Smart Livestock Systems”.
The session highlighted the differences between climate smart agriculture and climate smart livestock and aimed with a variety of presentations to answering the following question: What are the major opportunities and challenges to make livestock systems climate-smart?
Felix Teillard (FAO) – The role of livestock in adapting to climate change and building economic resilience in Zambia
Giel Scholtz (ARC – ZA) – Sustainable livestock production in the era of climate change through targeted interventions
Todd A. Crane (ILRI) – Science and policy priorities for climate smart interventions in the livestock sector
Lutz Merbold (ILRI) – Tier 2 greenhouse gas emission factors from livestock systems in East Africa
Harold Weepener (ACR) – Potential impact of climate change on livestock diseases
Edwin Mudongo (University of Cologne) – Exploring grazed ecosystems functioning and management options under extreme drought conditions in Limpopo, South
Jonathan Vayssieres (CIRAD) – AfricaLivestock mobility and climate smart landscapes in West Africa
Philip Thornton (CCAFS) – Evaluating climate-smart options in tropical livestock systems
Key messages from the session are:
- Climate Smart Livestock has some defined differences from traditional Climate Smart Agriculture, namely: Mobility, Multifunctionality and Nutritional value.
- Other important points to be considered in order to achieve CSL are: the potential of cross-breeding with indigenous species to achieve climate change adaptation, the potential increase in livestock disease and the need for early warning systems (extreme climatic events), the issue of landscape analysis and better integration of crop and livestock in mixed systems, improved market access when intensifying and avoiding negative feedback such as increasing the number of livestock. For interventions to be adopted, their contribution to the three pillars of CSA should be assessed and tradeoffs been highlighted at different scales. Incentives should be tailored for all stakeholders.
- Learn from eachother: Meaning that conventional climate smart agriculture has lots of knowledge on climate change (CC) adaptation while there the information for livestock remains limited. On the other hand, a lot is there in terms of mitigation and a dedicated session should be organized at the next CSA conference to facilitate knowledge transfer from both side.
- Investment in good data is necessary, especially in developing countries as often evidence based advice is hampered by the limited number of on the ground studies only (particularly mitigation and adaptation). Default data derived from production systems in high-income countries often do not reflect the reality of smallholder systems in developing countries. For instance, IPCC Tier 1 GHG emissions factors can lead to important overestimations of GHG emissions of smallholder livestock keepers and likely also from pastoral systems in drylands.
- There is a diversity of technologies available to makes livestock systems climate smart, and these have been there for a long time. However, technologies differ largely for the system these Are applied to as well as for the region these are aimed at. A synthesis of tools per region and system should be anticipated – and the key question on how to bring this knowledge to the farmer remains unanswered?
- There is a large body of evidence on CSL interventions increasing productivity while decreasing emission intensity (emissions per unit of products). Combining those interventions with a reduction in animal number would allow to decrease absolute GHG emissions. However, increased productivity often has the opposite effect – buying more animals – and cultural pressure prevents the reduction of animal number in many systems. There is a need to closely study intensification dynamics, the influence of resource constraints and the effect on animal number in order to address absolute reductions in GHG emissions.