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Regional livestock modeling for climate change adaptation and mitigation in Southern Africa

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Regional livestock modeling for climate change adaptation and mitigation in Southern Africa

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Presentation by Dolapo Enahoro and Karl M. Rich at the Southern Africa Towards Inclusive Economic Development (SA-TIED) Programme – A Scoping Workshop on Climate Change Pretoria, South Africa, 4 February 2019

Presentation by Dolapo Enahoro and Karl M. Rich at the Southern Africa Towards Inclusive Economic Development (SA-TIED) Programme – A Scoping Workshop on Climate Change Pretoria, South Africa, 4 February 2019

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Regional livestock modeling for climate change adaptation and mitigation in Southern Africa

  1. 1. Regional Livestock Modeling for Climate Change Adaptation and Mitigation in Southern Africa Dolapo Enahoro and Karl M. Rich Southern Africa Towards Inclusive Economic Development (SA-TIED) Programme – A Scoping Workshop on Climate Change Pretoria, South Africa, 04 February 2019
  2. 2. Outline Background Modeling the livestock sector using global models Knowledge gaps Options for SA-TIED Climate & Energy research Environmental impact assessments Pasture-climate change impacts Potential outputs
  3. 3. Background Incomes and the demand for animal-source foods are generally growing in low- and middle- income countries (LMICs) There’s a need to understand emerging opportunities for food security, poverty reduction, economic development, etc. Much also unknown about the implications for vulnerable landscapes and the world’s poorest populations.
  4. 4. The IMPACT model Source: Rosegrant et al., 2014 The IMPACT Model System •Model traditionally better suited to the crop sector •Work is ongoing to improve model’s capacity for livestock sector assessments •IMPACT is a system of linked models of global agriculture simulating multi-country multi-commodity markets, water and crop models
  5. 5. Using IMPACT for livestock modeling • Key applications & advantages :  Simulate economic change, climate change effects and adaptation strategies relevant to livestock sector  Project demand, production, trade of livestock-derived foods (LDF), and their welfare impacts  Assess systems and regions for growth potential, response to shocks, competitiveness, trade-offs, etc.  Assess countries/regions’ technology, investment and policy options in the context of megatrends.
  6. 6. Recent results from global livestock modeling • LDF to be higher in selected LMICs in 2050; Much of new demand (>=40%) to be met through imports. This has implications for household incomes and nutrition (Enahoro et al., 2018) • Investments to increase livestock productivity in South Asia, sub-Saharan Africa to improve food security and producer incomes while limiting GHG emissions, agricultural resource use; • Market-focused interventions lead to increased needs to manage environmental impacts (Enahoro et al., 2019). • Production systems matter! Climate change mitigation policies will be most efficient when they are targeted directly to the source of emissions (Havlik et al., 2014).
  7. 7. What else do we want to know? Production(millionsoftonnes) LMICs Year HICs •Where will ASF and feed demand growth occur the most? •Where and how will the needed ASF and feeds be produced? •How will climate change affect outcomes? •What policy considerations are needed to promote sustainability?
  8. 8. Exploring intervention options 0 1 2 3 4 5 6 7 8 0 1000 2000 3000 4000 5000 6000 methane (CO2eq)/kg milk Milk yield (kg/lactation) Largest improvements in low producing animals FAO 2013, Herrero et al 2013 • Exploiting yield gaps may be key to achieving environmental benefits in ruminant-based systems • It may also play an important role in achieving food security.
  9. 9. Livestock and climate change in Southern Africa: the Issues • 8.1 million poor people in Southern Africa derive livelihoods from livestock (Robinson et al., 2011; FAOStats, 2010 est.); the poorest likely eat the least ASF, but are most vulnerable to CC impacts on agriculture; PLK in country’s population Share of PLK in region Share of cattle & shoat stocks Share of chicken and pig heads Share of emissions (CO2 equiv.) Botswana 14% 4% 6% <1% 9% Lesotho 27% 7% 5% 4% 4% Namibia 31% 8% 12% 5% 14% South Africa 12% 77% 76% 88% 71% Eswatini 29% 4% 2% 2% 3% Table 1: Selected statistics
  10. 10. Research Options • Linking IMPACT’s climate change simulations to results from the G-Range model (Boone et al., 2017) Food security and resource use changes associated with pastoral and agro-pastoral livestock production • Environmental impact assessments and resource use analysis in IMPACT + CLEANED (Pfeiffer et al., 2016) Land use and environmental impact outcomes of future CC- Income interactions in Southern Africa
  11. 11. OPTION ONE: Linking IMPACT to G-Range LinkageCould we link IMPACT simulations of climate change impacts to G-Range results to assess for Southern Africa: • Livestock demand, production and trade • Feed demand and pasture availability • Food security • Producer and consumer incomes These linkages will however not include feedbacks
  12. 12. The G-RANGE Model The G-Range model: • Moderate complexity spatial ecosystem model quantifying global changes expected in rangelands under future climates Key results (Boone et al., 2017): • Baseline and mean changes in ensemble results using 7 GCMs are presented for 13 global rangeland ecosystem responses under RCP 4.5 and 8.5 Climate change to have substantial impacts on forage production; shifting distribution of livestock production • Populations already food insecure may become increasingly so.
  13. 13. Sample Spatial Assessments Figure: Regional percent changes in selected attributes from ensemble simulation results in 2050 (Boone et al., 2017)
  14. 14. OPTION TWO: Linking IMPACT-CLEANED The CLEANED tool: Spatially explicit simulation tool that computes land use and environmental impacts based on parameters of livestock production defined by the user (Pfeifer et al., 2016). resampled open access data IMPACT defined livestock categories (dairy cattle, meat cattle, shoat, pigs and chicken) GIS pre-processing code Production and land allocation module Water impact Greenhouse gas Bio-diversity Soil nitrogen balance Land use change module Pfeifer et al., 2016
  15. 15. Preliminary Results from IMPACT-CLEANED simulations in East and West Africa In Tanzania, land did not pose a constraint to livestock sector transformation under key macro scenarios Outcome depends on substantial crop productivity gains and shifts of arable land into feed grain and fodder production Alternatively, about twice as much land area needed for crop monocrop to support livestock production in 2050. Analysis for Burkina Faso showed LDF production implied by the model projections require higher productivity gains than producers currently attain or aspire to.
  16. 16. Proposed activities Options Key steps/outputs 1. IMPACT-CLEANED (environmental impact assessment) Parameterize CLEANED for relevant Southern Africa countries Identify (through stakeholders) macro- scenarios of relevance to the region Assess impacts of identified scenarios on land use, feed use and food security 2. IMPACT-G- RANGE (rangeland modeling) Collate key results of climate scenarios previously quantified in IMPACT and G-Range Analyze important complementarities and trade-offs associated with rangeland systems production 3. Combination or other ??? Table 2: Potential outputs
  17. 17. This presentation is licensed for use under the Creative Commons Attribution 4.0 International Licence. better lives through livestock ilri.org
  18. 18. Our work at ILRI on livestock sector foresight analysis has received financial support from CGIAR Research Programs: - Policies, Institutions and Markets - Livestock - Climate Change, Agriculture and Food Security Bi-lateral donors: - The Bill & Melinda Gates Foundation - US Agency for International Development (USAID) Acknowledgements
  19. 19. Key References • IMPACT: Robinson, S., Mason-D’Croz, D., Islam, S., Sulser, T. B., Robertson, R. D., Zhu, T., … Rosegrant, M. W. (2015). The International Model for Policy Analysis of Agricultural Commodities and Trade (IMPACT): Model description for version 3. IFPRI Discussion Paper 01483 (IFPRI Discussion Paper No. 1483). Washington, DC. • CLEANED: Pfeifer, C., Morris, J., & Lannerstad, M. 2016. (2016). The CLEANED R simulation tool to assess the environmental impacts of livestock production (Livestock and Fish Brief No. 18). Nairobi, KENYA. • G-RANGE: Boone, R. B., Conant, R. T., Sircely, J., Thornton, P. K., & Herrero, M. (2018). Climate change impacts on selected global rangeland ecosystem services. Global Change Biology, 24(3), 1382–1393. https://doi.org/10.1111/gcb.13995

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