CCAFS Low emissions development (LED) activities funded by USAID
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Presentation by Lini Wollenberg, Low Emissions Development Flagship Leader at USAID offices in Washington September 24 2018
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CCAFS Low emissions development (LED) activities funded by USAID
- 1. Lini Wollenberg, CCAFS Low Emissions Development Flagship September 24, 2018 An update on CCAFS LED Activities funded by USAID
- 4. USAID support 2016-2018 Towards implementation of mitigation • Scholarship program for graduate students to quantify emissions in food loss and waste • Livestock MRV Tier 2 RUMINANT model • Agroforestry MRV 3. CLIFF-GRADS Fellowships 1. MRV 2. NDC support Feasibility and investment assessments • Vietnam • Kenya
- 5. 1 MRV of Livestock emissions Collaboration with UNIQUE Forestry, GRA and FAO • Review of MRV practices: report and workshop (2017)* • Compilation of practices, in progress (to be completed 2018) • MRV Resource Platform (2018) • Activity gap filling guidance, workshop (2018)* and report (2019) *USAID supporrted
- 6. Why improve MRV of livestock emissions? • 92 developing countries included livestock emissions in their NDCs • Yet most developing countries use Tier I approaches that generally do not capture mitigation • Most countries are still designing MRV for mitigation of livestock emissions Source: Wilkes et al. 2017
- 7. 1.1. Review of country practices (2018) 1. What are current MRV practices for livestock emissions? 2. What are the barriers and opportunities for improvement? Reviewed data for 140 developing countries; conducted interviews with 20+ countries Wilkes et al. 2017 French and Spanish versions also available
- 8. Survey results on IPCC criteria for MRV: Transparency, consistency, comparability, completeness and accuracy (TCCCA) • Moderate transparency: Only 99 reported activity data used, 117 reported emissions factors used. • Completeness– Good for CH4 (139 parties reported enteric fermentation, 134 manure management CH4); moderate for N20 (115 parties manure and 116 for soil). • Good comparability- all used IPCC guidelines • Moderate consistency: 82 used consistent time series, 37 parties were inconsistent. 21 reported one year only • Low accuracy - 119 out of 140 developing countries (85%) used Tier I For Tier 2 users, 16 parties did not update emission factors; only 5 used updated emission factors 89 parties - no analysis of uncertainty
- 9. Activity data: Gaps and mixed data sources Wilkes et al. 2017
- 10. Chile Colombia Ethiopia Indonesia Philippines Vietnam Human resource allocation to inventory work Institutional structures for inventory related research Weak links with national data providers (e.g. statistics agencies) Lack of data on diverse farm conditions Limited capacities for Tier 2 research Sustainability of finance for inventory agencies Finance for activity data collection or emission research Practical constraints to inventory improvement
- 12. 1.2 Activity Data: expert workshop Hague July 2018 • Shifting to Tier 2 requires regularly updated activity data that most developing countries do not yet collect • Demand for guidance for NDC and MRV developers on practical methods for estimating activity information
- 13. Country needs for activity data What? • Tier 2 and NDCs, but basic Tier 1 data gaps also exist (e.g. population stocks, age bands) • Definitions / characterization of systems • Core variables: population, live weight, weight gain, milk yield,diet, manure management systems • Dynamic and relevant to developing country conditions: - Regularly updated activity data for different production systems - Reflect reduced emissions (BAU scenarios) - Seasonality Guide to be completed by June 2019.
- 15. • RUMINANT will allow Colombia to use separate emission factors for different livestock production systems, which emit according to their productivity and efficiency. • This allows the inventory to capture mitigation effects, which is necessary for MRV of Colombia’s livestock NAMA. • By moving to an advanced inventory methodology, Colombia has achieved the level of MRV rigor necessary to attract climate finance for its NAMA. 1.3 Use of RUMINANT model to estimate methane emissions from livestock in Colombia (1) Photo: N Palmer, CIAT
- 16. • The RUMINANT model is a “Tier 3” approach to estimate methane (CH4) from enteric fermentation in livestock. • RUMINANT was validated for CH4 emissions from livestock in the tropical lowlands (Cauca Valley) for seven diets. • Good correlation observed between measured (polytunnel) and RUMINANT CH4 estimates. Use of RUMINANT model to estimate methane emissions from livestock in Colombia (2) Comparison between measured enteric methane emissions (solid circles) to those simulated by RUMINANT model (open circles).
- 18. 2. MRV of Agroforestry IPCC guidelines note that trees outside forests “should be included when they are a significant component of total changes in biomass stocks”(IPCC 1996, 5.13). • Yet agroforestry is often difficult to detect due to small land areas, unclear or overlapping institutional mandates, multiple land use classifications, and a lack of dedicated programs to build capacity or collect data. . Review Methods • Review of UNFCCC documents NCs (N=147), NDCs (N=147) REDD+ strategies (N=73) and NAMAs (N=264). • Interviews of key informants in 12 countries.
- 19. Agroforestry MRV- country needs Key findings • 40% of developing countries (59/147) proposed agroforestry in NDCs. • Highest interest in Africa (71%),then Americas (34%), Asia (21%) and Oceania (7%). • 71% (105/147) National Communications mentioned agroforestry or interventions that could include agroforestry. • 79% (42/53) countries with REDD+ explicitly included agroforestry in REDD+ efforts Source: Rosenstock et al. in press
- 20. Agroforestry MRV- reporting (1) 1. Countries overwhelmingly use Tier 1 approaches to quantify carbon stocks and carbon stock changes in the LULUCF sector (84%, 95/113 countries’ NCs) 2. Only 18 countries reported using some Tier 2 approaches. 3. REDD+ countries often use a mix of tiers when estimating forest carbon baselines 4. Representation of land uses at appropriate resolution is a precondition for the application of more accurate carbon stock change estimate
- 21. 5. Agroforestry that meets forest definitions more likely to be captured in reporting. • Relatively few countries provided a quantitative estimate of the carbon in non-forest trees in the inventory. 16 countries gave a quantitative estimate of either: • the number of trees (e.g. 300,000 trees in Nepal to 405,104,918 trees in Niger) or • the areal extent of trees outside forests (e.g. 250 ha in Nauru to 2.2 million ha in Tunisia). 6. Agroforestry in GHG inventory reports, still overall lacking • elaboration of woody biomass types and • presentation of subcategories of land-use types and GHG removal sources in supplementary tables. Agroforestry MRV- reporting (2)
- 22. Constraints and enabling conditions for MRV of agroforestry Rosenstock et al. In press.
- 23. Agroforestry MRV: National case studies in Vietnam and Colombia Developed estimates of C benefits of agroforestry and costs for implementation for Vietnam’s revision of the Nationally Developed Contribution (final revision scheduled March 2019). In Colombia, defined a pathway for integrating and monitoring tree- based systems, with a specific focus on agroforestry, under the developing Forestry NAMA. With the Colombia Ministry of Environment (MADS) and IDEAM (the institute responsible for GHG MRV). Made technical recommendations for trees on farms definitions and technical input for the construction and definition of categories Piloted use of cost-effective way to identify lands including agroforestry using ‘Collect Earth’ (cheap, crowd sourced, Google Earth Engine) in both Vietnam and Colombia. Results were positive, but challenges remain.
- 25. 3. Support for Countries’ NDCs Feasibility of rice LED options and investment plan for AWD in Vietnam Comprehensive, comparative analysis of potentially viable LED practices and their supporting interventions within the rice supply chain Geographic suitability Barriers Incentives, enabling conditions Costs, benefits and risk analysis 1. Domestic investment plan for AWD and mid-season drainage 2. Outline for international investment proposal for AWD Policy gap analysis Identification of policy levers to incentivize adoption Quantification of investment needed Identification of international funding sources Investment plan for AWD Prioritize interventions, identify instruments to encourage large- scale adoption Slides courtesy of Tran Van The
- 26. 3.1. Policy gap analysis o In policy development & implementation: Ambitious targets and limited financial resources (domestic, international support, private); especially for infrastructure, irrigations system; o Linkages and collaboration: Poor linkages in policies (inter-regional linkages, multidisciplinary; project to project); o Capacity building: Limited knowledge, readiness from local and private stakeholders in GHG reduction (LEDs); o Economic benefits vs social, environment and politic benefits: Low benefits and low or no support for private sector rice production o Performance and scaling: Good performance/test but lack esources for replication o Land tenure and large farm model: Slow moving land use policy for rice for investment 3. Results Slides courtesy of Tran Van The
- 27. 3.2. Policy levers for AWD in rice production 3. Results GHG mitigation on rice production GHG mitigation project (3119/BNN- KHCN, 2011) National green growth strategy and action plan ( 1393/QD- TTg, 2014) Action plan to response to climate change in agriculture (819/QĐ-BNN- KHCN, 2016) INDC (2015) Plan to implement NDC in agriculture (7028/BNN- KHCN, 2016) Restruc- tured rice project (1898/QD- BNN, 2016) AWD YY N N YYY Y YY SRI YY N N YYY Y YY ICM YY Y Y YYY Y Y MSD N N N YYY N - Compost YY Y Y YYY Y - Reduced nitrogen by SA YY N N YYY Y Y Biochar Y N N YYY Y - Slides courtesy of Tran Van The
- 28. 2.3. CBA on AWD in MRD 3. Results - 5,000.00 10,000.00 15,000.00 20,000.00 An Giang Kien Giang Soc Trang Average Costs (1000 VND/ha/season) AWD None - 10,000.00 20,000.00 30,000.00 An Giang Kien Giang Soc Trang Average Net benefit (1000 VND/ha/season) AWD None 30,000.00 35,000.00 40,000.00 45,000.00 An Giang Kien Giang Soc Trang Average Revenue (1000 VND/ha/season) AWD None
- 30. 4. Support for Countries’ NDCs Feasibility of livestock LED options and investment plan in Kenya and Ethiopia (Ericksen, using Dickhoefer et al., 2014)
- 31. Improving feed quality to reduce emissions intensities: Improvements in feed quality to increase productivity • Supplemental fodder from improved forage species – Mixed crop-livestock. (26-28% reductions in emission intensities for lactating cattle Opio et al 2016) • Supplemental feeding with concentrates –dairy (20- 27% reductions in dairy, Opio et al.) • Managed grazing – extensive pastoral (similar to improved feed quality?) • Analyzed profits to be made at farm level, based upon data collected from field visits with farmers in five counties. • Evaluated requirements for investment in a project to support yield positive returns over a five-year time span Source: Polly Ericksen, ILRI and John Kashangaki, SBA Africa Ltd 2018
- 32. Summary of findings: change in milk yield and monthly profit margin County Milk production per cow (kg/litres) with fodder Change in daily milk yield Profit margins with fodder intervention (KES) Change in monthly profit margins Worst case Best case Worst case Best case Murang’a 7 20 186% 16,158 33,558 108% Nyeri 6 15 150% 16,383 23,883 46% Uasin Gishu 6 15 150% 9,043 22,223 146% Kiambu 12 22 83% 53,267 63,800 20% Nyandarua 5 13 160% 7,625 23,158 204% Average 7.2 17 146% 20,495 3,325 105% Source: Polly Ericksen, ILRI and John Kashangaki, SBA Africa Ltd 2018
- 34. Fodder production can generate greater revenue and reduce emissions • Both milk yields and profit margins improve • GHG emissions intensities can reduce • 8 to 24% (FAO and NZAGGRC) or up to 0.46 metric tons CO2 equivalent with conservative adoption rates. • Brandt et al suggests reductions up to 26- 31%, if combine forages with concentrates Source: Polly Ericksen, ILRI and John Kashangaki, SBA Africa Ltd 2018
- 36. Call for Food Loss and Waste Proposals https://ccafs.cgiar.org/sites/default/files/career/attachments/CLIFF- GRADS%20call%20for%20applications%20FLW%202018-2019%20final_0.pdf
- 37. Conclusions: Where are countries in preparedness for mitigation? (1) MRV 1. MRV systems for livestock and agroforestry are moderate to weak, but seem to be heading in the right direction Livestock emissions accuracy is a concern, but many moving to Tier 2. Sensitivity to pasture feeds’ mitigation impact is possible with Tier 3. N2O needs attention. Agroforestry- increasingly visible, especially on forest lands; trees on farms are gap. Address resolution of scale as precondition for activity and emission factor data. Guidance needed?? Some countries are ahead, so learning can be accelerated with exchange. Need multi-country leadership 2. Biggest need is access to activity data: linkages among statistical systems is essential; remote sensing; crowdsourcing; include supply chains. 3. UNFCCC reporting drives institutional incentives for action, and institutional actors are clear. Strong impact pathway. 4. Need for multiple country leadership
- 38. Conclusions: Where are countries in preparedness for mitigation? (2) Feasibility and investment planning 1. Strong evidence for profitability and incentives for both AWD in rice and improved livestock fodder; although returns relative to other sectors not analysed. 2. But business and investment cases are messy, based on limited data and understanding, no consistent method 3. Feasibility and investment were highly focused spatially in intensive production areas, suggesting these might also be focal areas for MRV and investment case development. 4. Impact pathway is less clear given need for multiple actors and ministries; complex and competitive climate finance environment, gap between research and implementation. How to strengthen this?
- 39. https://ccafs.cgiar.org/flagships/low-emissions-development https://ccafs.cgiar.org/our-work/capacity-enhancement#.W5bZ1i2B3EY CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS) Thank you!
- 40. Interventions to reduce emissions intensities • Manure management • Biodigesters for methane capture – (zero grazing) dairy • Manure storage in covered heaps – mixed crop-livestock
- 41. Interventions to reduce emissions intensities • Improved animal husbandry • Reduce chronic disease burden of intestinal parasites – all systems • Reduce age at slaughter – pastoral systems
- 42. Cross Cutting Themes • Degree of market orientation is major precondition for upgrading • Even with market orientation, low milk prices inhibit investment in upgrading • Small land size as major limitation • Low trust and accountability of input services
- 43. Improved Forages • Barriers Low availability of land (B) – paddocks? Diversified cropping strategies (M, I?) Low accessibility of improved planting material (M) • Potential incentives? Field trials to improve farmer awareness Investments to stimulate fodder seed Financial evaluation of specialization vs diversification • NB: AI and dairy meal become more attractive when basal diet improves
- 44. Biodigestors • Barriers High upfront cost (M) Maintenance requirements (I) Slurry transport (B) • Incentives Household energy source (direct benefit) Improved household health (direct benefit) Farmer innovation on slurry transport ?
- 45. Managed Grazing in Rangelands • Barriers Require high institutional governance capacity (O) Expansive landscape commitment (O,B) Long time horizon to see substantial carbon sequestration effects (B) • Incentives Improve market access to drive intensification Couple with improved herd management and health
- 46. Interventions to reduce emissions intensities • Improvements in Feed Quality to increase productivity • Supplemental fodder from improved forage species – Mixed crop-livestock • Supplemental feeding with concentrates – dairy • Managed grazing – extensive pastoral
- 47. Interventions to reduce emissions intensities • Manure management • Biodigesters for methane capture – (zero grazing) dairy • Manure storage in covered heaps – mixed crop-livestock
- 48. Interventions to reduce emissions intensities • Improved animal husbandry • Reduce chronic disease burden of intestinal parasites – all systems • Reduce age at slaughter – pastoral systems
- 49. Domestic investment plan for AWD Policy gap analysis Quantification of investment needed Consultation with finance experts; Identification of international funding sources Feasibility analysis on AWD (separated study): • Geographic suitability • Barriers to adoption • Identify incentives and enabling conditions to encourage large-scale adoption Identification of policy levers to incentivize adoption Analysis of costs, benefits and risks 2. Methodology
- 50. 2. Methodology Province AWD Convention An Giang 40 20 Kien Giang 40 20 Soc Trang 40 20 Total 120 60 Costs and benefits determination Field data collection CBA application Cost efficiency calculation MAC Estuimated abatement rate of GHG (tCO2eha-1) Potential scale analysis (ha) Estumated abatement optential of GHG (M. tCO2e) Reculate cost effectives (CE) and abatement potential Sensitive analysis and scenario (low, medium and high) Sample taken from field survey MAC applied to determine cost of GHG reduction on rice RRA and PRA for data collection SWOT, bottleneck analysis Slides courtesy of Tran Van The
- 51. 6 4 Argentina • 8 agro-ecological and climatic regions • Breeding and fattening systems identified/region • Production systems modeled (activity, diet, reproduction and production) • Aggregate results cross-checked against regional, census and agricultural production data. Bolivia • 3 climatic regions (altiplano, valles and tropics) • Cattle and sheep sub-classes (e.g. dairy cattle, non-dairy cattle, young cattle and oxen) using expert opinion in region. • Data on feed rations, apparent digestibility of forage and feed and other production data (e.g. milk yields, live weights)/region obtained from publications or government agencies. Diverse structures for Tier 2 classification
- 52. RECOMMENDATIONS 6 5 1. Consider updated Tier 2 approaches using activity and livestock production data that reflect changing livestock systems and their productivity 2. Improve synergies among statistical systems, other livestock data systems and MRV 3. Share country experiences on priorities for livestock MRV system development 4. Develop methods for addressing gaps in activity data
Editor's Notes
- Accuracy: No systematic over- or under-estimatation, uncertainties are reduced as far as practicable Transparency: Assumptions and methodologies clearly explained
- Major challenges: clarifying and refining land-use definitions to include agroforestry; defining institutional mandates as they relate to agroforestry; lack of access to high-resolution satellite imagery, strengthening technical capacities and resources for data collection improving transparency in reporting Recommendations: Develop accessible approaches for representation of lands with agroforestry Create guidelines for agroforestry reporting to improve transparency Develop carbon stock change and emission factor data and databases relevant for reporting requirements Assess the institutional arrangements needed to include agroforestry in MRV Research and practical guidelines on linking national and project-level MRV Create mechanisms that increase the likelihood of continued funding for continuity o
- Representation of agroforestry on multiple land uses is one of the limitations found in the assessment and we test a new cheap and crowd sourced way to look at identify agroforestry systems with Google Earth Engine. Results were positive but also suggest a few challenges. We identify a few key steps to refine including use of local knowledge in designing rules for identify systems. The Government of Colombia has shown significant interest in this approach, when briefed on it and ICRAF hopes to present it in detail to them in Quarter 4 of 2018.
- CCAFS is now collaborating with a number of countries, including Vietnam, Colombia and Kenya to implement their NDCs. Vietnam for example, according to their NDC plans to implement alternate wetting and drying or mid season drainage in 1.7 mil ha We are supporting comparative analysis of options for reducing emissions and the development of an investment plan to provide the basis both for policy change and investment in scale-out (at the national level) and submission of proposals for climate finance. In Kenya we supported similar work. In Columbia we have supported modeling emissions usingthe RUMINANT model and the development of better emission factors. Important lessons are being learned from these experiences that we hope can inform NDCs and pave the way for other countries to also be successful.
- Investment plan for AWD should be implemented for 900 thousand hectares, contribute in 10.97 million tCO2e, produced added net benefit of 8,540 billion VND (371.36 million US$/yr.) as compared to conventional rice cultivation in 2030.
- Dairy is the fastest growing sub-sector of Kenyan agriculture 4% of Kenya GDP; about five billion kg of milk annually Ten low emissions development (LED) interventions for the livestock sectors in Kenya and Ethiopia were reviewed (Ericksen and Crane 2018). From these, one intervention was selected for further analysis— improving availability of quality feeds for the smallholder dairy subsector, specifically by improving forages. The rationale for this is that access to adequate feed availability and quality are a prerequisite to any other productivity improvements such as improved breeds. The intervention is most suited to intensive and semi-intensive dairy because it requires collection and, ideally, storage of fodder to feed to animals that reside on farms, with limited grazing. Currently, intensive and semi-intensive dairy production produce about 65% of the total emissions from dairy production. Improved fodder, especially if combined with legumes or dairy concentrates, could reduce emissions intensities per animal or litre of milk by up to 30%. Stimulating more livestock producers to invest in improved fodder production will require external investments, as the current rates of adoption are very low. Here we outline a clear articulation and rationale for investment in improved forage production and use by smallholder dairy producers, as well as a feasibility assessment of such an investment. We look at two levels of investment—by farmers themselves and for project implementation. We present a business case as follows. First, we present the overall economic context of Kenyan smallholder dairy production. Second, we detail an analysis of the possible profits to be made at farm level, based upon data collected from field visits with farmers in five counties. Third we evaluate what would be required to make an investment in a project to support yield positive returns over a five-year time span. Last, we review the role of other value chain actors and the support they might provide. The farm level modelling suggests that there are considerable improvements in productivity and profitability to be made across the five counties if farmers were to invest in on-farm fodder production. In three of the counties this is true even in the low price and production scenario. At the level of a project across three of the counties, the results show that after the second year, the project’s benefit would be greater than the annual investment cost assuming minimal risk. We caution that a lot of extension support on fodder production, together with support to develop fodder markets, would also be needed. Currently, neither cooperatives nor the large processors are providing as much support as they could in this area.
- It is estimated that the project will break even by the second year after initiation The dairy production system, fodder variety and optimal herd size for different sized parcels under fodder farming is determined. 3. Data on farm operations from three counties is presented. 4. The feasibility analysis of fodder management is conducted for three counties where a project might be implemented. 5. The fodder project investment cost–benefit analysis at macro level is presented. 6. Overall, the public investment cost of implementing a program targeting up to 30,000 smallholder households over a five-year period is estimated. Key informant interviews were conducted with purposively selected farmers from Kenya’s central region (Murang’a, Kiambu, Nyandarua and Nyeri counties) and Rift Valley region (Uasin Gishu and Nakuru counties). The information is used to present basic cost–benefit analysis for one representative household from each of the five counties. The households own varying parcels of land and numbers of dairy cattle, sell varied quantities of milk and consume part of their production. All households are assumed to face varying market prices. Each household can produce varying quantities of milk, a portion of which is sold through dairy cooperatives or producer associations. Note that in many counties expanding fodder farming will reduce area available for food crops. For each county, three cases are presented. A base case (Case A) where the household derives income from current on-farm operations as is; a second case (Case B) where the household cultivates fodder, facing an opportunity cost of land; and a third case (Case C) where the household cultivates another crop instead of fodder. The cases are derived from the reality of the farmers interviewed in each county. For each case, two scenarios are evaluated—a best case with higher milk outputs and prices, then the worst case, in order to see how sensitive the farm revenues are to changes in output and price. We note that output–price fluctuations are the greatest risk smallholder farmers face. These prices can fluctuate by up to 30%, and so many farmers choose to diversify their farming activities. Since there are five counties, the total number of cases analysed is 15, each with two scenarios. The cases are presented in the following order: Murang’a county, Kiambu county, Nyandarua county, Nyeri county and Uasin Gishu county.
- The public investment cost of implementing a programme targeting up to 30,000 smallholder households over a fiveyear period is estimated at USD3.3 million (this excludes the individual farmer investment in improved feeding inputs). This investment can be justified as it is estimated that within a three-year period it would be paid back through higher productivity and income for the targeted beneficiaries.
- Joint initiative of CCAFS and the GRA ~USD 10,000 fellowships For early-career scientists and graduate students from developing countries To conduct applied research on climate change mitigation in agriculture and quantification of agricultural greenhouse gases Generates novel climate change research on smallholder farming systems and facilitates South-South knowledge exchange At least half of all fellowships to women Collaboration with GRA initiated in 2017, building on CCAFS CLIFF network Support provided by CGIAR Trust Fund and bilateral donors, including New Zealand and USAID
- And of course, this only indicates the agenda. The real work is in implementation. CCAFS is now collaborating with a number of countries, including Vietnam, Colombia and Kenya to implement their NDCs. Vietnam for example, according to their NDC plans to implement alternate wetting and drying or mid season drainage in 1.7 mil ha We are supporting comparative analysis of options for reducing emissions and the development of an investment plan to provide the basis both for policy change and investment in scale-out (at the national level) and submission of proposals for climate finance. In Kenya we are doing similar work. In Columbia we have supported modeling future emissions and the development of better emission factors. Important lessons are being learned from these experiences that we hope can inform the NDC partnership and pave the way for other countries to also be successful.
- Text Box 12: Different ways used by selected countries to structure application of the IPCC Tier 2 equations Argentina:56 The country was divided into 8 regions, based on agro-ecological and climatic factors. In each region, a number of breeding and fattening systems was identified. Data to characterize production systems in terms of activity, diet, reproduction and production in each system were then procured from literature, and entered into a model structured around regions and production systems. The resulting preliminary model was then refined using other data sources, and the aggregate results cross-checked against regional, census and agricultural production data. Bolivia:57 Cattle populations in three climatic regions (altiplano, valles and tropics) were identified according to the agro-ecological zonation of different departments (sub-regions) in the country. For cattle and sheep, the population was stratified into sub-classes (e.g. dairy cattle, non-dairy cattle, young cattle and oxen) based on consultations with livestock production experts in each region. In each region, data on feed rations and apparent digestibility of forage and feed was obtained from publications, and other production data (e.g. milk yields, live weights) were obtained from publications or government agencies. Georgia:58 Common cattle breeds in Georgia include late maturing breeds (the Georgian Mountain and Red Mingrelian) characterized by low weight, low productivity and high milk fat content, as well as several high-productive early maturing breeds that were imported in the previous century. The IPCC equations were populated separately for early and late maturing breeds at different life stages using published data and expert opinion. Expert opinion was used to estimate the proportion of each breed in the total cattle population. Mongolia:59 Although Mongolia has diverse indigenous breeds of livestock, a small number of breeds dominate the total population of each livestock type. Published breed characterization studies were referred to, and used along with expert judgement of livestock experts and IPCC default factors to develop a single Tier 2 emission factor for each type of livestock in the country. Results were compared with Tier 2 factors from China.
- A summary of the recommendations, including points made during discussion, are as follows: Expand support for analysis, identification and implementation of livestock mitigation options Include economic analysis Identify innovations for mitigation technologies, including those related to energy efficiency Ensure mitigation is farmer-focused Support inter-ministerial discussion Countries seeking to measure emission reductions through the national GHG inventory should consider adopting a Tier 2 approach that uses regularly updated activity and livestock production data to reflect actual, changing livestock systems and their productivity at appropriate scales. Conduct an international review of Tier II approaches and implied emission factors to identify gaps in information Produce a standard format for MRV, which countries can elect to use or not. Improve accuracy, transparency and sustainability of MRV. Consider reporting emissions intensities in addition to emissions. Strengthen synergies between improvements in statistical systems or other livestock data systems and improvements in MRV Identify key data needs Map out data sources & needs for MRV, and identify, develop and strengthen institutional links to NDCS, NAMAS other higher profile objectives like SDGs Identify key stakeholders Allows communication & bottom up approach Instil a willingness to share data based on common goals and mutual benefits Increase synergies among private-public-academic actors. Consider building an inter-ministerial agenda for climate Government mandate Public interest Support research collaboration Support sharing of experience among countries on prioritized aspects of livestock MRV system development Produce a resource based on country case studies, good practices and innovations to demonstrate what “good enough” MRV can be. Examples of collecting Activity Data, specific parameters, how to deal with data gaps, use of different approaches, tools and innovations Demonstrate approaches and decision trees to meeting minimum requirements for MRV, based on transparency in reporting of uncertainties, sensitivity testing and developing pathways for further improvements. Provide opportunities for face-to-face networking, including regional meetings. Promote innovation at different level of mitigation action and MRV Explore compatibility of MRV between levels (project, jurisdictional, sectoral, national) and effective institutional arrangements Focus on MRV that supports mitigation actions Provide a decision tree and examples of best practices for developing baselines, sources of information (including use of mixed sources) and dealing with limited data availability Embed MRV in knowledge management that supports farmers’ information Session 9: The final session provided the participants with further information on the proposed timeline for the draft white paper. The White Paper will be presented as a draft at the GRA Livestock Research Group Meeting in Washington April 2017 and finalized in time for SBSTA in Bonn May 2017. A short executive summary document of the White Paper will be produced as well as infographics, blogs such as AgChats and possibly a podcast. The suggestion was made to map the paper’s recommendations to the UNFCCC guidelines to aid reporting. The White Paper will be shared on the sponsoring organizations’ websites under a creative communication license. Participants said that it would be useful to have the final White Paper translated into Spanish and French. A resource guide to minimal standards based on examples of good practices will also be explored. Actions points