Livestock-Climate Change CRSP Annual Meeting 2011: MLPI-2 Project Update (J. McPeak)


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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.

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  • Trend of weekly livestock prices averaged across all markets since January 2010. Demonstrates a fairly consistent difference in price between grade of animal. This price differential can be used to assess the profitability of livestock fattening with supplemental feeding. The LMIS data combined with information on quality and prices of supplemental feeds can assist in developing a profitable enterprise using least cost rations
  • The NIRS system allows rapid assessment of the quality of feeds, fodders, and indirect measurement of livestock diet quality using livestock manure. For common feeds and grains (corn, wheat, millet, sorghum), the systems come with equations provided by the manufacturer. For supplemental feeds native to Mali, equations will need to be developed by assessing the quality of the feeds with traditional wet chemistry methods and then doing spectral scans of the supplemental feed materials using NIRS. Then, chemometric software can be used to develop multivariate prediction equations that take advantage of correlation between the wet chemistry data (nitrogen, digestible organic matter) and the spectral signatures of the paired feed materials. After a robust equation is developed, the NIRS can be used for rapid scanning of the supplemental feeds for quality analysis. If outliers are detected, the samples can be submitted for wet chemistry analysis, scanned and added to a new equation to improve the predictions in the future.Equipment was purchased in MLPI-1 and MLPI-2 to assist in brining state-of-the-art equipment to IER and IPR for nutrition analysis. IPR was targeted so that students could be trained in the use of the equipment and to train them in understanding least cost rations in order to provide personnel to the emerging feed industry in Mali and as personnel for national laboratories such as at IER.
  • IER has begun development of equations for predicting quality of native grasses and legumes that can be used as supplemental fodders. Wet chemistry has been conducted on the majority of the collected samples and spetra data has been collected with the PERTEN NIRS. Data have been staged for equation development and these will be conducted in late may. The equations will be shared with the IPR lab.
  • Study area encompasses a large portion of the rangeland and mixed rangeland/cropping areas in the semi-arid region of Mali.
  • ASTER satellite imagery was used for the analysis. It has a resolution of 15m. Period of ASTER data collection goes from 2000 to present. Priority areas were identified in the study area for the initial purchase of images. In the future additional images will be purchased for outside the priority areas. A classification algorithm that was developed for a similar study in East Africa was modified to be used in this study. The classification detects water holes that have clear water in the imagery and also has capabilities to detect water holes with murky or discolored water.
  • Green boudaries depict the imager boundaries for the 91 Aster scenes that were purchased for the initial water hole classification. The red areas indicate the priority areas that were identified for the initial purchase of imagery.
  • Field protocols will include: 1) verification of the accuracy of the satellite image classification 2) characterization of the waterholes (e.g., circumference, water quality/appearance, photographs, depth, etc.), and 3) periodic monitoring for changes in depth over time to validate the simulation model. Steps for data collection have been discussed and documented, and draft field datasheets were prepared. Training will be conducted in June or July for data collection and verification activities.DNPIA personnel have met with administrators for the PADESO (Livestock Development Support Programme in Western Sahel) and the Azawak Projects administrators to discuss their participation in the water monitoring project. Both projects agreed to provide personnel and motorbikes for data collections. Hameye A.A. Cissé from the PADESO project staff will lead data collection for the Sokolo Zone and Alwaata Sidiky of the Azawak Project will lead activities for the Ansongo Zone. 
  • During TAMU’s visit to the IER and IPR labs during February 2011, 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. This equation was adapted from the small ruminant work previously done at the Grazingland Animal Nutrition Lab at Texas A&M University. In the coming months, the performance of the equation will be evaluated as the equation is evaluated for Malian small ruminants. Data collected from the first round of Malian feeding trials will also be added to this calibration to fine tune the calibration for Malian small ruminants.
  • Livestock-Climate Change CRSP Annual Meeting 2011: MLPI-2 Project Update (J. McPeak)

    1. 1. Mali Livestock and Pastoralist Initiative – Phase 2<br />LCC CRSP Principal Investigator Meeting <br />April 26-27, 2010 <br />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 <br />Development or the U.S. government.<br />
    2. 2. US Partners for MLPI – 2<br />Texas AgriLife Research/Texas A&M University (TAMU)<br />Syracuse University (SU)<br />University of Wisconsin (UW)<br />University of Arizona (UA) <br />South Dakota State University (SDSU)<br />
    3. 3. Malian Partners for MLPI –2<br />Observatoire du Marche Agricole (OMA)<br />Direction Nationale des Productions et des Industries Animales (DNPIA)<br />Institut d'Economie Rurale (IER)<br />l'Institut Polytechnique Rural (IPR)<br />
    4. 4. Activity 1. Livestock Market Information Systems (LMIS)<br />Responsible Partners:<br />Texas A&M <br />DNPIA <br />OMA<br />
    5. 5. Livestock Market Information System (LMIS)<br />Implement a Livestock Market Information System to define and develop a broader information network to improve market opportunities and reduce risk <br />Integrate system into the current livestock market data streams<br />Take advantage of information technologies (cell phones, internet) to provide near real-time data<br />Improve and expand the analytical, reporting, and geographical relevance of the data<br />
    6. 6. LMIS Methodology<br />Use cell phones to send data from markets to make information more timely<br />Use of a central server for access of data via cell phone SMS, internet, and other methods <br />Allows access by all stakeholders<br />Provides transparency in the marketplace<br />Training of market monitors and stakeholders in use of the system<br />
    7. 7. Computer<br />(<br />Web<br />/<br />Email<br />)<br />LMIS Architecture<br />Internet<br />Country <br />Country Analysis <br />Data<br />Country LMIS<br />DNPIA<br />Data<br />and Reporting<br />Mirror Server<br />Mali Main Server (OMA)<br />Smart<br />phone<br />Computer<br />Cell<br />Smart<br />phone<br />Cell <br />(<br />Web<br />/<br />Email<br />)<br />Information Delivery<br />Data Collection<br />
    8. 8. LMIS Status<br />The LMIS data is currently being collected at 32 markets, providing coverage to all of Mali<br />Livestock grading and coding procedures have been developed for cattle, sheep, goats, camels, donkeys, and horses. <br />Examining ways to include commodities and livestock by-products (meat, milk, hides, feeds, fodders, etc), <br />
    9. 9. Price Differentials<br />Data from the LMIS indicate strong price differentials within and across the markets<br />Fat animals vs. thin animals<br />Spatial differences <br />Price peaks can occur near religious holidays and festivals<br />Price differentials offer opportunities to demonstrate economic feasibility of livestock fattening enterprise<br />
    10. 10. Cattle Price Differences by GradeAverage of all Markets<br />~450 CFA = 1 USD<br />
    11. 11. Activity 2. Market Chain Analyses<br />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<br />Examine household marketing and migration decision making by pastoralists for livestock<br />Conduct participatory studies of livestock movement. <br />Responsible partners:<br />Syracuse<br />IER - Direction<br />IPR<br />
    12. 12. Value Chain Surveys<br />Modified the value chain surveys used in Ethiopia by the International Livestock Research Institute (ILRI). <br />Four of the surveys were modified for use in Mali. These included:<br />an expert informant survey<br />a broker survey<br />a trader survey<br />a cooperative survey. <br />
    13. 13. Value Chain Surveys<br />Enumerators have been trained and the surveys are currently being conducted in northern Mali.<br />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. <br />
    14. 14. Household Surveys<br />
    15. 15. Reasons for not Selecting Livestock Fattening as an Investment<br />
    16. 16. Activity 3. Supplemental Feeding <br />Further develop capabilities for conducting rapid scans to assess the nutritional contents of supplemental feeds using Near Infrared Reflectance Spectroscopy (NIRS)<br />Workshops on the use of the quality analysis for herd and risk management decision making (least cost rations)<br />Best management practices for storage of feeds/fodders <br />Responsible partners:<br />Syracuse <br />IER - Sotuba<br />IPR<br />Texas A&M <br />Univ. of Arizona<br />
    17. 17. Laboratory Upgrades<br />Added bench top and portable Near Infrared Reflectance Spectroscopy (NIRS) Instruments to both IER and IPR ruminant nutrition laboratories<br />Added capabilities for in-vitro digestion and fiber analysis<br />Other equipment upgrades include grinders, water filtering equipment, scales, computers, and drying ovens<br />
    18. 18. Forage and Fodder Nutrition<br />The IER animal nutrition lab has initiated NIRS equation development for livestock forages.<br />Samples have been collected for 38 legumes and 12 grasses at various growth stages. <br />Wet chemistry analyses were conducted for dry matter (DM), organic matter (OM), crude proteins, fat, cellulose, energy, and minerals (Ca, Na, P, K) <br />Spectra were scanned using the Perten DA7200 NIRS machine. <br />
    19. 19. Activity 4. Risk Management Studies<br />Use of remote sensing and mapping to assess livestock mobility and access to forage resources in Mali<br />Livestock mobility and conflict management<br />Planning for livestock mobility – Interactive mapping of transhumance corridors in Mali<br />Responsible partners:<br />University of Wisconsin <br />Syracuse<br />IER - Direction<br />
    20. 20. Greenness and Mobility<br />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)<br />Using an increasing window around selected centerpoints, MODIS data from 2000-2010 has been completed. <br />
    21. 21. Greenness and Mobility<br />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. <br />After controlling for latitude and time into the growing season, no significant linear trend is found across the 11-year study period. <br />
    22. 22. Conflict Management<br />A participatory program has been initiated to identify causes which underlie farmer-herder conflict and solutions at the level of commune communities. <br />Commune-wide workshops have been conducted to introduce stakeholders to the goals and objectives of the project. <br />
    23. 23. Activity 5. Water Monitoring for Livestock<br />Identify surface water holes for livestock using satellite imagery<br />Conduct simulation modeling of changes in water levels in water holes<br />Verify image classification and simulation model outputs<br />Map water status and provide interactive website of model outputs<br />Responsible partners:<br />South Dakota State University <br />DNPIA<br />Texas A&M<br />
    24. 24. Study Area<br />Area stretches West to East across north- central Mali<br />Areal Extent<br />0.35 million Sq. Km<br />Approximately a third of Mali<br />
    25. 25. Satellite Image Analysis<br />A total of 91 ASTER satellite images downloaded for Mali<br />65 images covering Priority Areas<br />26 images outside the Priority sites<br />Total satellite image area covers more than 90% of the study site<br />Images subjected to classification algorithm that identifies clear water holes and potential waterholes with murky water<br />
    26. 26. Entire Study site – 91 Aster images<br />
    27. 27. Field Protocols for Water Monitoring<br />Developing protocol for field teams to conduct ground truthing of image analysis<br />Verify accuracy of the classification<br />Identify any false positives<br />Opportunistically add any false negatives during field navigation<br />Characterization of the waterholes (e.g., circumference, water quality/appearance, photographs, depth, etc.)<br />Leveraging field verification with other projects (PODESO and Azawak Projects)<br />
    28. 28. Activity 6. Monitoring Nutritional Status Of Livestock Feeds And Animals<br />Develop capabilities in Mali to assess quality of feeds and fodders through standard lab methods and Near Infrared Reflectance Spectroscopy (NIRS)<br />Develop capability to monitor nutritional status of livestock using livestock manure<br />Assess livestock diet quality<br />Assist in developing supplemental feeding strategies<br />Responsible partners:<br />IER - Sotuba<br />Texas A&M <br />IPR<br />Syracuse<br />Univ. of Arizona<br />
    29. 29. Diet Quality for Livestock<br />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. <br />Equation was adapted from the small ruminant work previously done at Texas A&M University. <br />
    30. 30. Diet Quality for Livestock<br />Performance of the equation for Malian small ruminants will be conducted in the coming months.<br />Additional spectral data will be added to the equation as diet trials are conducted this summer<br />
    31. 31. Diet Quality for Livestock<br />Feeding trials have been conducted for cattle and sheep <br />Feeding trials are being developed for camels<br />Training has been conducted for both IER and IPR on feeding trials and diet quality equation development<br />
    32. 32. Capacity Building<br />Training both government and education personnel in use of new technologies<br />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<br />Since August 2010, MLPI has trained 236 men and 34 women on MLPI technologies<br />
    33. 33. Leveraging<br />LCC-CRSP RIVERS project<br />Post-doc from Embrapa– Brazilian Agriculture Research Corporation at TAMU<br />Development of nutritional balance software for small ruminants<br />Improvement in information delivery to producers<br />Will be at TAMU for 1 year beginning in July 2011<br />Collaborations with NGOs and other Livestock projects<br />
    34. 34. Questions?<br />