An update on the Livestock-Climate Change CRSP's Mali Livestock and Pastoralist Initiative-2 Project and project status report. Presentation given by J. McPeak (Syracuse University) at the Livestock-Climate Change CRSP Annual Meeting, Golden, CO, April 26-27, 2011.

1. Mali Livestock and Pastoralist Initiative – Phase 2 LCC CRSP Principal Investigator Meeting April 26-27, 2010 This presentation was made possible by the United States Agency for International Development Bilateral Mission in Mali and the generous support of the American people through Grant No. 688-A-00-10-00131-00.The opinions expressed herein are those of the authors and do not necessarily reflect the views of the U.S. Agency for International Development or the U.S. government.

2. US Partners for MLPI – 2 Texas AgriLife Research/Texas A&M University (TAMU) Syracuse University (SU) University of Wisconsin (UW) University of Arizona (UA) South Dakota State University (SDSU)

3. Malian Partners for MLPI –2 Observatoire du Marche Agricole (OMA) Direction Nationale des Productions et des Industries Animales (DNPIA) Institut d'Economie Rurale (IER) l'Institut Polytechnique Rural (IPR)

4. Activity 1. Livestock Market Information Systems (LMIS) Responsible Partners: Texas A&M DNPIA OMA

5. Livestock Market Information System (LMIS) Implement a Livestock Market Information System to define and develop a broader information network to improve market opportunities and reduce risk Integrate system into the current livestock market data streams Take advantage of information technologies (cell phones, internet) to provide near real-time data Improve and expand the analytical, reporting, and geographical relevance of the data

6. LMIS Methodology Use cell phones to send data from markets to make information more timely Use of a central server for access of data via cell phone SMS, internet, and other methods Allows access by all stakeholders Provides transparency in the marketplace Training of market monitors and stakeholders in use of the system

7. Computer ( Web / Email ) LMIS Architecture Internet Country Country Analysis Data Country LMIS DNPIA Data and Reporting Mirror Server Mali Main Server (OMA) Smart phone Computer Cell Smart phone Cell ( Web / Email ) Information Delivery Data Collection

8. LMIS Status The LMIS data is currently being collected at 32 markets, providing coverage to all of Mali Livestock grading and coding procedures have been developed for cattle, sheep, goats, camels, donkeys, and horses. Examining ways to include commodities and livestock by-products (meat, milk, hides, feeds, fodders, etc),

9. Price Differentials Data from the LMIS indicate strong price differentials within and across the markets Fat animals vs. thin animals Spatial differences Price peaks can occur near religious holidays and festivals Price differentials offer opportunities to demonstrate economic feasibility of livestock fattening enterprise

10. Cattle Price Differences by GradeAverage of all Markets ~450 CFA = 1 USD

11. Activity 2. Market Chain Analyses Conduct a market chain study for livestock markets in Mali that would document the flow of livestock from local markets to terminal and border markets Examine household marketing and migration decision making by pastoralists for livestock Conduct participatory studies of livestock movement. Responsible partners: Syracuse IER - Direction IPR

12. Value Chain Surveys Modified the value chain surveys used in Ethiopia by the International Livestock Research Institute (ILRI). Four of the surveys were modified for use in Mali. These included: an expert informant survey a broker survey a trader survey a cooperative survey.

13. Value Chain Surveys Enumerators have been trained and the surveys are currently being conducted in northern Mali. Surveys are being conducted in LMIS market areas so that the value chain analysis can be matched with the data being gathered in the market monitoring activity.

14. Household Surveys

15. Reasons for not Selecting Livestock Fattening as an Investment

16. Activity 3. Supplemental Feeding Further develop capabilities for conducting rapid scans to assess the nutritional contents of supplemental feeds using Near Infrared Reflectance Spectroscopy (NIRS) Workshops on the use of the quality analysis for herd and risk management decision making (least cost rations) Best management practices for storage of feeds/fodders Responsible partners: Syracuse IER - Sotuba IPR Texas A&M Univ. of Arizona

17. Laboratory Upgrades Added bench top and portable Near Infrared Reflectance Spectroscopy (NIRS) Instruments to both IER and IPR ruminant nutrition laboratories Added capabilities for in-vitro digestion and fiber analysis Other equipment upgrades include grinders, water filtering equipment, scales, computers, and drying ovens

18. Forage and Fodder Nutrition The IER animal nutrition lab has initiated NIRS equation development for livestock forages. Samples have been collected for 38 legumes and 12 grasses at various growth stages. Wet chemistry analyses were conducted for dry matter (DM), organic matter (OM), crude proteins, fat, cellulose, energy, and minerals (Ca, Na, P, K) Spectra were scanned using the Perten DA7200 NIRS machine.

19. Activity 4. Risk Management Studies Use of remote sensing and mapping to assess livestock mobility and access to forage resources in Mali Livestock mobility and conflict management Planning for livestock mobility – Interactive mapping of transhumance corridors in Mali Responsible partners: University of Wisconsin Syracuse IER - Direction

20. Greenness and Mobility An investigation was conducted into the scaling thresholds for livestock mobility and seasonal access to forage resources (as indicated through MODIS Normalized Difference Vegetation Index [NDVI] data) Using an increasing window around selected centerpoints, MODIS data from 2000-2010 has been completed.

21. Greenness and Mobility Multiple regression analysis indicates that the distance at which no further gains in forage access occurs generally increases with latitude and decreases with days into the growing season. After controlling for latitude and time into the growing season, no significant linear trend is found across the 11-year study period.

22. Conflict Management A participatory program has been initiated to identify causes which underlie farmer-herder conflict and solutions at the level of commune communities. Commune-wide workshops have been conducted to introduce stakeholders to the goals and objectives of the project.

23. Activity 5. Water Monitoring for Livestock Identify surface water holes for livestock using satellite imagery Conduct simulation modeling of changes in water levels in water holes Verify image classification and simulation model outputs Map water status and provide interactive website of model outputs Responsible partners: South Dakota State University DNPIA Texas A&M

24. Study Area Area stretches West to East across north- central Mali Areal Extent 0.35 million Sq. Km Approximately a third of Mali

25. Satellite Image Analysis A total of 91 ASTER satellite images downloaded for Mali 65 images covering Priority Areas 26 images outside the Priority sites Total satellite image area covers more than 90% of the study site Images subjected to classification algorithm that identifies clear water holes and potential waterholes with murky water

26. Entire Study site – 91 Aster images

27. Field Protocols for Water Monitoring Developing protocol for field teams to conduct ground truthing of image analysis Verify accuracy of the classification Identify any false positives Opportunistically add any false negatives during field navigation Characterization of the waterholes (e.g., circumference, water quality/appearance, photographs, depth, etc.) Leveraging field verification with other projects (PODESO and Azawak Projects)

28. Activity 6. Monitoring Nutritional Status Of Livestock Feeds And Animals Develop capabilities in Mali to assess quality of feeds and fodders through standard lab methods and Near Infrared Reflectance Spectroscopy (NIRS) Develop capability to monitor nutritional status of livestock using livestock manure Assess livestock diet quality Assist in developing supplemental feeding strategies Responsible partners: IER - Sotuba Texas A&M IPR Syracuse Univ. of Arizona

29. Diet Quality for Livestock A fecal NIRS equation for predicting diet quality constituents of free ranging small ruminants was installed on both the IER Sotuba and IPR Katibougou NIRS machines. Equation was adapted from the small ruminant work previously done at Texas A&M University.

30. Diet Quality for Livestock Performance of the equation for Malian small ruminants will be conducted in the coming months. Additional spectral data will be added to the equation as diet trials are conducted this summer

31. Diet Quality for Livestock Feeding trials have been conducted for cattle and sheep Feeding trials are being developed for camels Training has been conducted for both IER and IPR on feeding trials and diet quality equation development

32. Capacity Building Training both government and education personnel in use of new technologies Developing training programs for both implementation of the new technology and how to best use technology to reduce risk and improve decision making by stakeholders in Mali Since August 2010, MLPI has trained 236 men and 34 women on MLPI technologies

33. Leveraging LCC-CRSP RIVERS project Post-doc from Embrapa– Brazilian Agriculture Research Corporation at TAMU Development of nutritional balance software for small ruminants Improvement in information delivery to producers Will be at TAMU for 1 year beginning in July 2011 Collaborations with NGOs and other Livestock projects

34. Questions?