development and evaluation of models and methods to ... fivims pilot study workshop ii, july 4-6,...

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A FIVIMS Pilot Study Conducted in the Republic of Mali

Second Planning Workshop

Palais des Congres, Bamako, Mali July 4-6, 2 000

Institute of Rural Economy (IER) Institute of Sahel (INSAH)

Texas A&M University

January 2 001

Mali FIVIMS Pilot Study Workshop II, July 4-6, 2000, Bamako, Mali, page 2.

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A FIVIMS Pilot Study Conducted in the Republic of Mali


Findings and Results


ACRONYMS ACT Almanac Characterization Tool AGROSOC Agro-Socio-Economic Research APCAM Agricultural Chamber CAE Agri-Business Center CAFPD Analysis and Development Policy Center CAT/GRN Cell of Regional planning/Natural Resource Management CERPOD Center for Population Study and Research for Development CILSS Permanent Interstates Committee for Drought Control in the Sahel CIRAD International Agronomic Research Cooperation Center for Development CPS Statistics and Planning Unit CMDT Malian Company for Cotton Industry Development CNRA Agricultural Research National Center CRA Agricultural Regional Chamber CRRA Agronomic Research Regional Center CRSP Collaborative Research Support Program DIAPER Permanent Diagnostic Project DNAMR National Direction for Rural Development DRAER Regional Direction for Planning and Rural Equipment DRAMR Regional Direction for Rural Development DRAS Regional Direction of Health DNSI National Direction for Data Processing and Statistics DRCN Regional Direction for Nature Preservation ECOFIL Economic System ESPGRN Production System and Natural Resource Management Team GDSS Global Decision Support System GIS Geographic Information System GOM Government of Mali GTOS Global Terrestrial Observing System FIVIMS Food Insecurity and Vulnerability Information and Mapping Systems FLIPSIM/TIES Farm Level Income and Policy Simulation/Technology Impact Evaluation

System ICRAF International Center for Research in Agro-Forestry ICRISAT International Crops Research Institute for the Semi-Arid Tropics IER Institute of Rural Economy IFAD International Fund for Agricultural Development IIED International Institute for Environment and Development IMPACT Impact Methods to Predict and Assess Contributions of Technology INRSP Public Health National Research Institute INSAH Institute of Sahel INTSORMIL International Sorghum and Millet IPR Rural Polytechnic Institute IRD Research for Development Institute ISFRA Institute Superior of Formation and Applied Research KIMS Knowledge Management Information System LaboSEP Laboratory Soil-Water-Plant


MAP Policy Analysis Matrix MASM Mali Agricultural Sector Model MATA Multilevel Analysis Tool for the Agricultural Sector MEEU Ministry of Equipment, Environment and Urbanism MRD Ministry of Rural Development NRM Natural Resource Management OHVN Niger’s Upland Valley’s Office OMBEVI Malian Office for Cattle and Meat PAM Policy Analysis Matrix PAP Pastoral Management Project PASAOP ex-PNRA, Agronomy Research National Program PIRL Woody Resources Inventory Project PIRT Terrestrial Resources Inventory Project PNT Natural Phosphate of Tilemsi PNVA National Program for Agriculture Vulgarization ROCAFREMI West and Central African Millet Research Network (WCAMRN) ROCARS West and Central African Sorghum Research Network (WCASRN) ROSELT Long Term Ecological Monitoring Observatories Network SANREM Sustainable Agriculture and Natural Resource Management SG 2000 Sasakawa Global 2000 SEP Continuous Monitoring and Evaluation System UNDP United Nations Development Program WAICENT Worldwide Agricultural Information Center ZAER Rural Expansion and Animation Zone ZR Rural Expansion Zone


Table of Contents Acronyms 3 Executive Summary 7 Acknowledgments and Appreciation 7 Introduction 8 Background 10 Overall Objective 11 Specific Objectives 11 Main Objectives for the Three Planning Sessions 12 Format and Product of the Individual Planning Sessions 12 Plenary Session Introduction and Status of Implementation of the FIVIMS Pilot Study Plans 13 Welcome by Host Institution 14 Dr. Alpha S. Maiga, Director General, IER(no) 14 Report on the National Task Force on Models for Food Security 14 Dr. Bino Teme, Scientific Director, IER 14 Report of the Technical Advisory Committee for the FIVIMS Pilot Study 15 Mr. Alpha Kergna, ECOFIL/IER 15 Human Nutrition Data for Overall Food Security Impact Assessment 15 Ms. Geraldine Kouadio, FAO/Mali 15 Objectives and Outcomes of the Second Workshop. Format and Procedures for the Workshop 16 Dr. Neville Clarke, Texas A&M University 16 The Almanac Characterization Tool for Mali. Presentation and Discussion of Application 17 Mr. Beau Bush, Texas A&M University 17 Discussion 18 Session A The Use of Remote Sensed Data, Biophysical Models and Spatially Explicit Analysis to Assess the Impact on Natural Resources and Environment of Technology and Policy Options Affecting Food Security 19 Session B Agricultural Economic Models and Assessment of Impacts of The Impact of Technology and Policy Options. Interfacing Models and Building Capacity 29


Session C Factors Affecting Adoption of New Technology for Application to Heuristic Rule Making 39 Plenary Sessions Issues and opportunities transcending the planning sessions 49 Summary Reports and Discussion of Planning Sessions 49 Conclusion 53 List of Participants 54 Appendices 57 Appendix 1 58 Appendix 2 60 Appendix 3 64


Executive Summary Partners:

• Institute of Rural Economy • Ministry of Rural Development • Ministry of Environment • INSAH • AGRHYMET • FAO • SANREM West Africa Project

Acknowledgments and Appreciation The Institute of Rural Economy, INSAH, Texas A&M University and FAO-WAICENT are very grateful to the participants for their strong support of the workshop and whose contributions made this workshop a success. Appreciation is expressed for financial and in-kind support for the workshop provided by USAID - EGAD-AFS through the SANREM CRSP , FAO-WAICENT, INSAH, and the Mali Institute of Rural Economy. The team would like to extend their sincere appreciation to the different chairpersons and rapporteurs who conducted perfectly the intensive and numerous individual sessions of the workshop: Dr. Togola, Dr. Stuth, Dr. Nantoume, Dr. Lansry, Dr. Eddleman, Mr. Kergna, Dr. Niangado, Dr. Clarke and Dr. Tabo. This workshop would not have materialized without the full commitment and dedication of Alpha Kergna, agro-economist at IER. We are especially grateful and would like to give a special thanks for the support of the TMG team, especially Jorge Oliveira and their administrative assistant Mme Tangara.


Introduction Texas A&M University with its collaborators in the Institute of Rural Economy (IER) have been developing national and regional models for Mali and adjacent Sahelian countries to assess the impact of policy options and new technology for the last two years. These collaborative studies are being continued under the USAID SANREM CRSP (Sustainable Agriculture and Natural Resource Management / Collaborative Research Support Program) as the Global Decision Support System (GDSS). FAO and Texas A&M plan to further develop and test the utility of these models to aide decision makers in national governments to assess the status food security, evaluate options for interventions to improve food security, and, in doing so, to employ methods that will ensure sustainable use of natural resources. The Worldwide Agricultural Information Center of FAO (WAICENT) is an ongoing participant in the study. They are providing partial funding for the workshops. WAICENT has a major role in supporting the Food Insecurity and Vulnerability Information and Mapping Systems (FIVIMS) Secretariat by providing relevant data bases in an accessible form and methods for assessment of the status of food security and vulnerability at national, regional, and global levels. WAICENT is collaborating with Texas A&M to assess the models and analytic capacity emerging from the development of the global decision support system, using the study in Mali as a “real-world platform” for development and evaluation. A pilot study (an initial study in one country to develop methods) has been initiated in Mali with the Government of Mali (GOM) and other partners as an early step in the overall process of development and use of these methods. The results from these studies will be evaluated for use in other developing countries as they strive to meet the goals of the same international conventions, especially the Sahelian countries served by the Permanent Interstates Committee for Drought Control in the Sahel (CILSS). To include this goal of applying lessons learned in Mali to other member States of CILSS, the Institute of Sahel (INSAH) major program on Agro-Socio-Economic Research (AGROSOC) has operational objectives with main activities that will directly benefit from the assessment methods developed being developed by SANREM and FAO in these pilot studies. INSAH has therefore agreed to co-sponsor and host the planning workshops and to participate in the ongoing pilot study. To refine the targets and scope of proposed studies, national and regional partners a workshop was held in December 1999 to review, modify, and adopt plans for the pilot study (i.e. Report of the Planning Workshop of December 7-9, 1999, Volumes I and II, April 2000 at http://cnrit.tamu.edu/workshop/). Participants were asked to discuss their needs for analysis and assessment in these areas. The Texas A&M models were presented and their use discussed. Results from analysis of the impact of sorghum technology on Malian economy and environment were presented as a case study to illustrate the utility of the suite of models. National and regional partners discussed the utility of these systems and recommended ways in which their utility can be enhanced. The WAICENT databases and the Knowledge Management Information System (KIMS) were demonstrated during the first workshop. Workshop participants included a small cadre of advisors enlisted to participate in the evaluation of results and design of modification of products as the pilot study proceeds.


Major result of the workshop was the finalization of the plan of action that had been draft by the relevant Ministries and Offices of the Government of Mali, the Institute of Rural Economy, The UN Food and Agriculture Organization and Texas A&M (SANREM) on two prior occasions since May 1999. The original plan of action for the Pilot Study proposed further development of models through conducting several case studies involving scenarios relevant to planning for food security and natural resource management in Mali. In fact, several of these scenarios were completed in time for presentation at the December 1999 workshop. One component of this plan of action, which reflects the major findings and recommendations reached at the workshop, was the need of further development of the GDSS models with special emphasis on the integration of economic, environmental, and socio-cultural components into a holistic approach and with the participation of both an expanded team of scientists and users in accordance to the high priority that was attached to national capacity building. Case studies were to be defined in cooperation with collaborators and users that represent “real world” needs for impact assessment. The process of deliberation with our national partners has continued since the December workshop with two additional substantive engagements in February and May and intervening correspondence by email and telephone. The Malian Technical Advisory Committee has discussed the results of the December workshop and provided a report on their findings. These activities have identified a set of issues and opportunities that formed the basis of in-depth work sessions which were undertaken in this second workshop. The second workshop was more of a research planning engagement. Status reports were provided on interim activities since the last workshop by national partners, representatives of the Government of Mali and Texas A&M. In considering the recommendations from the first workshop, and interacting with national partners and users, it became clear that additional planning and discussion would help focus the next (more detailed) set of assessments on more specific needs of decision makers and on ensuring that the suite of models are further integrated as the next round of scenarios is undertaken. This is the second workshop on a collaborative research effort being sponsored by the USAID SANREM CRSP (Texas A&M), the Malian Institute of Rural Economy (IER), and the FAO Worldwide Agricultural Information Center (WAICENT). This second workshop was held at the Palais des Congres in Bamako, Mali from July 4-6, 2000 to further plan the details of the remaining studies and to evaluate progress since the December workshop. The workshop was successful in reaching numerous recommendations of the previous workshop, as reflected into the plan of action, at both political and technical level with 1) an integrated plan for further Development of Integrated Impact Assessment Models in a participatory process and in accordance with high priority for capacity building 2) the development of an integrated method for assessment of the status and trends of human nutrition and related methods to improve food security and reduce vulnerability as initiated between the FIVIMS Secretariat, UNDP and the GOM about the establishment of a national FIVIMS for Mali, 3) a strong commitment for the future establishment of the National Task Force on Models and Food Security 4) a promising step for the development of the involvement of regional organizations such as INSAH and AGRHYMET at the outset in the Mali Pilot Study, to ensure a successful transfer of knowledge and capability to other CILSS countries.


Background To provide improved methods to assess the impact of introduction and use of technology resulting from USAID investments in agricultural research, a suite of integrated interactive models was created for use in developing countries. Economic, environmental, and biophysical models were developed to provide a holistic evaluation of the impact of new technology or policy options. Studies were conducted in East and West Africa. In West Africa, the impact in Mali of the introduction of shorter season higher yielding sorghum varieties, ridge tilling for water retention, and enhanced use of inputs was estimated. Experimental data from INTSORMIL (International Sorghum and Millet) CRSP and ICRISAT (International Crops Research Institute for the Semi-Arid Tropics), involving national research and extension partners and farmers’ trials, provided estimates of costs of production and yields for both the current and new production systems. This case study drew on the accomplishments of the participants in the USAID INTSORMIL CRSP which include both U.S. university scientists and their colleagues in the Malian Institute of Rural Economy. In addition, vitally important information and insights were obtained from Malian Extension workers and representative NGOs in the country. Two partnerships are represented. First, was the collaboration with INTSORMIL scientists, which included sorghum breeders, agronomists, economists, and related disciplines in IER. Second, the development of the impact assessment models involved overlapping collaboration with IER economists and with the Institute of Sahel. Data from the research done by ICRISAT was also valuable to the overall assessment of research impact. The research involved acquiring relevant data bases and expert opinions through collaboration with national partners, establishing a spatial framework using GIS (Geographic Information System) methods to estimate production and environmental consequences of the technology and adaptation, and the use of crop simulation, economic sector and farm level models to estimate the economic and environmental consequences. Conservative estimates of adoption rates were developed through interviews of national research and extension workers and farmers. The results of development and evaluation of the suite of models in IMPACT (Impact Methods to Predict and Assess Contributions of Technology) provided proof of concept of the ability to use this new holistic approach to assessment of the impact of new technology or policy options. The results may be used broadly by developing countries, donors and research organizations to evaluate options, set priorities, and estimate outcomes. The ultimate beneficiaries of this analytic capacity are farmers in developing countries. Specifically, this case study applies to Mali and adjacent West African countries. The Food Insecurity and Vulnerability Mapping Information System has been established and housed in FAO to monitor progress toward achieving the goals of the World Food Summit. FAO has an interdepartmental working group dealing with progress towards achieving the goals of the Convention to Combat Desertification. FAO also houses the Global Terrestrial Observing System (GTOS) which monitors the status of natural resources on a global scale. The Government of Mali is organizing an integrated food security system for Mali and implementing a National Environmental Action Plan for Environment. FAO and the GOM are collaborating to


improve the national capacity to monitor and assess the impact of options to improve progress towards achieving the goals of these international conventions. The plan of action for the Pilot Study involves several components, each of which will be impacted by the planning sessions. These are: C Further development of the Global Decision Support System models with special

emphasis on the integration of economic, environmental, and socio-cultural components into a holistic approach. With current funding constraints, this will involve a focus on the Sikasso region where the aim is to conduct research involving a set of farms representing the commodity, climatic and biophysical diversity of the region. In this research, the data acquisition and analysis will be done concurrently for the three components of the GDSS. The results of this will be combined with the national and regional Agricultural Sector Model (ASM). Where possible, the goal is to link these studies with ongoing IER monitoring of multiple villages and households in the region and to link inputs and outputs of these studies to the more detailed analysis using the GDSS.

C As part of the development of the GDSS in Sikasso, case studies will be defined in

cooperation with collaborators and users that represent “real world” needs for impact assessment. These case studies will produce a specific set of relevant results. They will also be used as test platforms for the further development of the GDSS. This is consistent with the plan of action emerging from the December workshop.

C Studies relating ground based studies with satellite imagery to assess impacts on livestock

and grazing lands are planned. The objective is to develop improved utility of modern satellite imagery in better defining the status and utility of biomass and to develop improved predictive tools for satellite based agricultural early warning systems. These methods are also aimed at developing improved capacities to assess status and trends of ecosystem health as a result of land use and climate.

Overall Objective The overall purpose of the second workshop is to engage national and regional partners in further discussion leading to joint development of specific details for implementing the plan of work for the Mali FIVIMS. This will build on the results of the first workshop and two intervening engagements in February and May. Three Planning Sessions will be held in concurrent sessions with plenary sessions at the outset and end of the workshop. There are common general objectives and desired outcomes for the planning sessions. Specific Objectives The specific objectives of the second planning workshop are to conduct three interactive planning sessions and two plenary sessions on the status of the pilot study. The planning sessions deal with:


C The Use of Remotely Sensed Data, Biophysical Models, and Spatially Explicit Analysis to Assess the Impact on Natural Resources and Environment of Technology and Policy Options Affecting Food Security

C Agricultural Economic Models and Assessment of the Impact of Technology and Policy

Options - Interfacing Models and Building Capacity C Factors Affecting Adoption of New Technology for Application to Heuristic Rule

Making The two plenary Sessions are on Status of Implementation of Pilot Study Plans and includes:

• Summary reports and discussion of Planning Sessions

• Report of the Technical Advisory Committee

• Report of the National Task Force on Models for Food Security

• Status report on the Mali FIVIMS

• Final Synopsis and Future Plans Main Objectives for the Three Planning Sessions 1. Discussion and consensus on the underlying economic, biophysical, environmental, and

socio-cultural factors that are involved in assessment of the impact of technology and policy options for agricultural production and management of natural resources

2. Review and discussion of the current GDSS models and related models available or in

development for use in Mali and West Africa. The objective is to develop further understanding (capacity building) and to identify interrelationships between models

3. Identification of areas of most useful collaboration between partners and definition of

separate and joint areas of research for collaboration. Define these in terms of research objectives and resulting outcomes.

4. Extension of the current plan of action for the Mali FIVIMS Pilot Study by defining the

explicit experimental design for the three main components, including the time-phased contributions of each partner. Defining the participants and schedule for the segments of the collaboration. Considering the actions needed to define the interrelationship between models and data available or under development in Mali in relation to the GDSS.

Format and Product of the Individual Planning Sessions:


This was a three-day workshop. The first half-day was a plenary session and the last plenary session commenced at 11:00 on the third day and continued through the afternoon. The individual planning sessions involved most of two days of the three-day workshop. The three planning sessions involved national and regional collaborators as well as key operators and managers that will use the methodology being developed and evaluated in the pilot study. The goals and expected outcomes of these work sessions were described in individual terms of reference and provided separately to participants. The format for the planning sessions was informal with opportunity for extensive discussion. A key product of these discussions was the definition of the precise goals of the next case studies and of the role of the various partners in conducting and evaluating this research. The last half day was a session for summarizing the results of the planning sessions and reporting on and discussing the status of various activities involved in the Pilot Study or its implementation. Chairs, organizers, and rapporteurs were identified prior to the meeting. They were encouraged to budget the available time in the session to ensure that the objectives were achieved. The general objectives were provided above and they were further interpreted in the specific terms of reference for each session. By the end of the second day, each planning session had discussed and come to agreement in principle on their response to each of the objectives. At the end of the second day, there was a one hour plenary session in which the three planning sessions were asked to make a brief (20 minutes) presentation on issues and opportunities arising from their deliberations which transcend individual sessions and have potentially broader implications and applications. This provided opportunity to include these overarching issues as input to the drafting of the reports of individual work sessions. After recess on the second day, organizers, chairs, and rapporteurs of the individual planning sessions were asked to prepare a draft of the conclusions, recommendations, and research plans from the session for discussion by their groups on the following morning. The format of the report generally follows the list of objectives of the planning sessions. On the morning of the third day, the drafters presented the draft report to the full work session group for discussion leading to a consensus on its content. In the final plenary session on the third day, the report of each planning session was presented and discussed. Reports on related topics were included in the final plenary session. An overall synopsis of the workshop completed the meetings.

Summary of Agenda

Tuesday Wednesday Thursday

AMFirst Plenary Individual

SessionsIndividual Sessionsto Review DraftReport

PM IndividualSessions

IndividualSessions forConsensus &Summary

Brief Plenary forOverarchingIssues

Third Plenary forReports ofIndividual Sessions

Final Synopsis andFuture Plans


Plenary Session Introduction and

Status of Implementation of the FIVIMS Pilot Study Plans

The invited participants are shown in appendix_____. There were 49 participants in the first plenary session and 39 in the final session. They represented a variety of disciplines, backgrounds, areas of responsibility and current activities.

Welcome by Host Institution Dr. , Deputy Director General, IER (to change) Dr. ______, Deputy Director General of the Institute of Rural Economy welcomed the participants to the workshop. He briefly reviewed the accomplishments from the first workshop held in December 1999 and recognized the co-sponsors of the second workshop. He mentioned the case studies that have been completed and the ongoing research following the last workshop. He mentioned the integrated suite of models that bring together economic, environmental, and biophysical components of methods to assess the impact of technology or policy options as part of the toolkit for decision makers dealing with food security and sustainable use of natural resources. Report on the National Task Force on Models for Food Security Dr. Bino Teme, Scientific Director, IER Dr. Teme, Scientific Director of IER, also welcomed the participants to the workshop and expressed his appreciation for their efforts. He expressed optimism about the outcome of the workshop. He noted the importance of the concept of integrating the multiple models into a holistic approach for impact assessment and their use in assessing options for policy and technology as means of enhancing food security. He noted the importance of recognizing the multiple interests in Mali for using the models as they are developed and evaluated. He recognized that these multiple interests have as yet not been coordinated within the Government of Mali to provide a basis for sharing common experiences and developing coordinated approaches to analyses. He noted that a committee organized by Ministry of Rural Development (MRD) and the Statistics and Planning Unit (CPS) had initial meetings and were communicating together about available models and their uses. He noted that their objectives include comparing and contrasting these models and to eventually provide a capacity for determining the most appropriate models for the various tasks at hand. The broad use of models and the demonstration of their utility is part of the goal of this task force. He noted that the French International Agronomic Research Cooperation Center for Development (CIRAD) and the Netherlands are also contributing to the development of modeling capacity for Mali. Dr. Teme said that IER would organize and provide a Secretariat to provide a focal point for the further deliberations of the National Task Force on Models and Food Security, as was discussed at the December 1999 meeting. Later in the meeting, he identified Mr. Alpha Kergna as the


national coordinator for the model developments and appointed him to serve as the chairperson of this Secretariat. He suggested that the current committee on models would merge into the National Task Force. He noted the importance of broad participation in the task force and expected that IER and INSAH would have important convening roles with involvement of MRD/CPS. He noted that the Ministry of Equipment, Environment and Urbanism (MEEU) would need to be active participants in the task force as well as other elements of the Government of Mali. One of the major products of the National Task Force will be recommendations to the various ministries of government on methods to be used to monitor the status of food security and vulnerability and to evaluate options to meet the World Food Summit goals of reducing hunger by 50% in the year 2015. The models considered by the National Task Force will be part of the national system for information on food security and vulnerability. The FAO and other international organizations will advise the government on developing an enhanced capacity for monitoring and analysis. The Texas A&M project is a pilot study for developing models to assist in these objectives under the Food Insecurity and Vulnerability Mapping Information System (FIVIMS). Report of the Technical Advisory Committee for the FIVIMS Pilot Study Mr. Alpha Kergna, ECOFIL/IER The Technical Advisory Committee was formed prior to the December Planning Workshop on the Texas A&M project. Representatives from various parts of government and private sector have met to discuss the results of the last workshop and provide recommendations to the project as part of this planning activity. Mr. Alpha Kergna, chairperson of this committee, provided the following report. Insert here Alpha Kergna Report Human Nutrition Data for Overall Food Security Impact Assessment Ms. Geraldine Kouadio, FAO/Mali Ms. Kouadio is based in the regional office of FAO in Bamako and works with colleagues in the Ministry of Health on improving the status of information on status of human nutrition in Mali and the region. FAO is a co-sponsor of the workshop and collaborator on the related research to developed improved models for use by FIVIMS on a national and regional basis. Ms Kouadio expressed appreciation for the focus of the workshop on FIVIMS and provided a brief overview of the goals and objectives of this Secretariat that serves the World Food Summit. She noted the interest of FAO and The United Nations Development Program (UNDP) in promoting improved food security information systems for Mali, including the offer made following the December 1999 workshop to work with the government to develop an enhanced capacity in this area. She referred participants to the website for FIVIMS (http://www.fivims.net/) for definitions of food security in the broader sense. She noted the importance of the broader definition of factors that affect the status of human nutrition such as health status and capacity for health care service, cultural factors such as food


habits, and level of education. She recognized the obvious importance of availability and accessibility of food, noting the importance of seasonality on these factors. She reminded participants that the new human nutrition census is started and that new data from this would be available early next year. The important point is that to assess food security means knowing the status of human nutrition. It goes past availability and access to actual consumption and assimilation. Objectives and Outcomes of the Second Workshop. Format and Procedures for the Workshop Dr. Neville Clarke, Texas A&M University Dr. Clarke reminded the participants of the components of the Mali FIVIMS Pilot study and of the overall and specific objectives of the workshop. He provided an historical perspective of the project, beginning with the development and proof of concept of models using the Sorghum Millet Case Study, followed by the proposal and draft Plan for FIVIMS Pilot Study with GOM and IER leadership and resulting by the first planning workshop held in Mali in December 1999. He reviewed the important findings and actions resulting from the December workshop as followed:

• Develop better understanding and Capacity Building • Strengthen IER partnership - adding natural resource management and information

management • Solidify relationships with CILSS organizations - capacity building • Emphasis on soil and water management - linking biophysical and economic models for

threat of degradation of natural resources • Improved linkages between models • Packaging information and models for decision makers at various levels • Incorporating inputs from decision makers and collaborators • Acquiring and using improved information • More Participation by Partners – Second Workshop on technical engagement of

collaborators. Then, he presented the interim activities that occurred since the December workshop with 1) the revision of the draft plan for Mali FIVIMS, 2) the extension of the models and analysis, 3) the search of external funds for capacity building and model simplification, 4) the two missions to Mali for further planning and engagement with collaborators and 5) the initiation of the Second Technical Planning Workshop. Others parallel activities occurred, some as a direct result of the December workshop, with the offer by FAO to facilitate Mali FIVIMS, the CPS Committee on Models, the National Task Force and the initiation of new human nutrition and agricultural censuses. Products of the study include:

• The Mali ACT and Related Data Bases (e.g. presentation of Mr. Bush below) • Report of December Workshop, Volumes One and Two (http://cnrit.tamu.edu/workshop/) • Annual Report on The Decision Support System (SANREM II)

(http://cnrit.tamu.edu/IMPACT/)


• Prototype Models and Related Databases. Dr. Clarke ended his presentation with a reminder of the format, products and agenda of the workshop (i.e. appendices). The Almanac Characterization Tool for Mali. Presentation and Discussion of Application Mr. Beau Bush, Texas A&M University Mr. Bush, Texas A&M University did a presentation on the Mali ACT (Almanac Characterization Tool) and the Mali spatial sampling frame. The Mali ACT is a stand alone GIS (Geographic Information System) that comes with a relevant packaged set of geo-referenced data. The idea behind this application is to present the software and data in such a way that the user can begin to reap the benefits of a GIS with a minimum of training and gathering of data. The visual perspective of spatial data often allows for synthesis and clarity not obtainable otherwise. This allows the decision-maker to ask a better question and the answers to have more meaning. The query tools within the ACT are targeted for use in agricultural and natural resource management. The spatial data in the Mali ACT include gridded climate and modeled surfaces suitable for germplasm adaptation studies, soils, population density, elevation and its derivatives, land cover, and recent census and human nutrition information. These data are combined with infrastructure data (e.g., roads, rivers, towns, political units) in a seamless windows-based application. Additional spatial analysis tools are under development for the ACT that address the need to quickly assimilate and derive data without the need for commercial software, thus further empowering the decision maker. The Mali spatial sample frame was derived from the judicious use of several spatial datalayers. These include climate clusters and soil layers to create simulation zones, population density, political districts, crop use intensity, and a 5 km buffer around roads. As a result of combining these once disparate spatial datalayers, areas of similar composition can now be classified into unique groups. These unique groups can aid decision makers on where to collect data or concentrated research efforts based on population or other factors. One example is to take a point datalayer of known sample locations and overlay it onto the sample frame to see if defined areas of importance have representative locations. This would allow efforts to be concentrated in those areas that are missing representation, thus saving time and money. For more information on the ACT and on the Characterization, Assessment, and Applications Group (CAAG), please refer to the following links: http://chaparral.brc.tamus.edu:1223/Support/ and http://www.brc.tamus.edu/char/


The Mali Spatial Sample Frame: The Simulation Zones in the Sikasso Region

Discussion There was discussion about how to best measure the interface between agriculture and status of human nutrition. It was noted that there are difficulties in establishing explicit relationships because of other confounding factors such as status of health, education, etc. Focus on the Sikasso region places the first round of studies in an interesting region of Mali. Here are grown the largest quantities of cash crops and exports and yet the level of human nutrition is lowest of any region of Mali. This emerged as an area recommended for focused study over the next year of research. There was active discussion of the capabilities for analysis and information sharing provided by the ACT. There was interest in knowing other countries where ACTs exist. Most ACTs are in East Africa, a few in Southern Africa, Mali is the only West African country with an ACT at this time. There was a question about the level of decision-makers that would use the suite of models – and how decision-makers would use them. First, the models are intended to help decision-makers at varying levels of scale from multi-national to farm. Second, models don’t make decisions, they are a tool to help decision makers. Models may be more useful in planning (ex ante options) at the local levels. The importance of education on food security was stressed several times.


Session A The Use of Remote Sensed Data, Biophysical Models and Spatially Explicit Analysis

to Assess the Impact on Natural Resources and Environment of Technology and Policy Options Affecting Food Security

There were questions about the utility of the Texas A&M models at their present state of development. It was acknowledged that some models are more usable at this point than others. The recommendations for capacity building made at the first workshop were recalled as being of fundamental importance. A major joint proposal with TAMU and FAO has been developed seeking support for capacity building and packaging the models to be more user friendly. It was recognized that models need to be accessible at varying levels of decision making. The importance of the National Task Force (see above) was reiterated.

Co-Chairs: Dr. Meme Togola, IER / CRRA Sikasso Dr. Jerry Stuth, Texas A&M University Rapporteur: Dr. Hamidou Nantoume, IER – CRRA Kayes Participants: 1. Siaka Bagayoko IER / CRRA Sikasso 2. Djaby Bakary AGRHYMET/CILSS 3. Abou Berthe IER / ESPGRN - CRRA Sotuba 4. Beau Bush Texas A&M University 5. Mamadou D. Coulibaly IER / CRRA Sotuba 6. Paul Dyke Texas A&M University 7. Hamidou Nantoume IER / CRRA/Kayes 8. Mamadou Kabirou N’Daye IER / CRRA Niono - Coordinator National PSI 9. Zana Jean-Luc Sanogo IER / ESPGRN - CRRA Sikasso 10. Yaya Sidibe DRCN Sikasso 11. Jerry Stuth Texas A&M University 12. Meme Togola IER / CRRA Sikasso 13. Bakary Toure ME / STP – CIGQE - ATEH 14. Pierre C. Sibiry Traore IER / Labo SEP Sotuba-ICRISAT Purpose and Focus of the Planning Session: This work session was intended to bring together scientists from IER, INSAH, ICRISAT, and TAMU that will collaborate broadly in the areas indicated in the title of the session. It is envisioned that the IER Labo SEP (Soil-Water-Plant) at Sotuba with its multiple collaborators will be one significant focal point for our collaboration. The Texas A&M models and related spatially explicit analysis will be linked with related efforts by our partners to develop an integrated plan of work. We expect the Mali Almanac Characterization Tool (ACT) to be a significant existing and available input to further research. As shown in the general terms of reference, it was envisioned that the collaboration represented


by this work session was to being involved in all three of the major research components in the plan of action. Our intent was to compare current separate plans for research on agriculture and natural resources, which use these tools and define a more meaningful and committed collaboration. At the December 1999 workshop, it was noted that the models which address the environmental component of the holistic approach to impact assessment are not as well defined as those dealing with economic outcomes. This pertains not only to the GDSS, but to the state of science in general in this area. Since the overall goal is to provide a assessment tools that look broadly at the economic, environmental, and societal impacts of technology and policy options, we agreed that the environmental models need to be enhanced and then more effectively integrated into the total Global Decision Support System. With a better definition of these indicators of ecosystem health, it will then be more feasible to undertake case studies using the overall holistic approach. A related but distinct objective in the GDSS work plan is research to improve the utility of modern satellite imagery by relating the primary and secondary data from these sources to relevant ground based information and biophysical models for livestock, forage or rangelands, and crops. The product is intended to be an improved capability for interpretation of satellite imagery applicable to broad areas such as West Africa. If successful, this would improve current assessments of the status and trends in overall ecosystem health for parts of the world, which are at risk for environmental degradation. The GDSS approach is to link this more extensive assessment with the predicted impact of new technology or policy options derived from the suite of models under development. Generalities: The workshop began by self-introduction of participants and their current duties and interests in spatial analysis and biophysical modeling of cropping systems, rangeland production, animal performance and environmental impact in Mali with particular emphasis on the Sikasso region. An agenda and time schedule for topics to be discussed in the workshop was presented to participants by the co-chairs and all participants approved it. The agenda included the four objectives to be achieved by the workshop. Objective 1. Discussion and consensus of underlying economic, biophysical, environmental and socio-cultural factors involved in assessment of impacts of technology and policy options for agricultural production and management of natural resources Terms of Reference: Emphasis should be placed on discussing the variables that come into play in an overall assessment of the status of ecosystems at points in time and estimating historical and future trends. These variables should be compared to available information or research underway to provide data, which either measure or serve as proxies for these variables. This is part of a larger consultative process with experts from both developed and developing countries. The objective of this part of the session is to define the most important indicators of the health of fragile ecosystems in West Africa, identify the existing information and data for these indicators, and make plans to acquire, assess, spatially represent, and use this information as input to the GDSS.


Results: The session began with an overview of the framework developed for impact assessment and how spatial characterization and biophysical modeling feeds the process for economic analysis, environmental impact and potential adoption of technologies. Comments were made by each participant on perceptions of the issues concerning needs for spatial analysis, characterization of biophysical processes and environmental analysis in the Sikasso region, including on-going research by participants. A number of key issues were identified as summarize below:

• Quantifying the temporal cycle of diet quality of livestock diets by major resource zone and vegetation type and identifying critical nutrient deficits in livestock nutrient intake. There is a need of monitoring tools and software to assess livestock in various production systems that can help identify critical nutrient deficits and mediate deficits with least cost feeding solutions.

• Fertility-fallowing interactions for crop production. The question was raised of how

best can crops and livestock be balanced to provide more income to the farmer in a sustainable manner. The needs to develop methods to quantify forage available for livestock and tools to set sustainable stocking rates and manage their associated rangeland in the cropping regions and in low cropping regions are critical.

• Determining which breed of livestock is best integrated in the various production

systems and ecosystems of Mali to trying to match environment and genetic potential. There is a need to find a predictive model for animal production that allows them to simulate how a breed of livestock would fit a given environment and production system. Interest is higher in farm level simulations that allows exploration of the economics of given livestock production systems in a given environment.

• Rainfall flux and rangeland production with the need to put in place a prediction

system for rangeland for forage production and determine the role of by products (crop residue, processing by products) in meeting short fall in forage supply. This might allow to assess the need to develop supplement programs and determine how much rangeland is contributing to nutrient intake of the animals.

• Livestock and food security. Identification of role of livestock in food security is

major issue. Specifically, how to improve use of livestock to cushion losses in crop deficits. Livestock could fill the protein gap. What role can satellite imagery play in dealing with this issue?

• Soil fertility for economic and strategic use of lands to lead to efficiency of

production. Modeling of soils and degradation in cotton regions is key problem. How do we integrate livestock production with cotton farms and new farming systems in the region? What are the social and physical constraints? How to use the land in animal production and maintain the overall production system. Issue of sedentary people now are facing the issue of setting safe carrying capacity when they were once transhumance or migratory.


• Economic development and links to impacts on the environment, especially the

issues of the conventions. How do we reconcile the needs of the Conventions with Natural Resource Management (NRM) issues?

A number of point of interests were expressed on:

• Ways of improving the state of pastoralist and dealing with issues of watering point development, natural resource management (NRM) and the transborder issues of livestock between Ivory Coast and Southern Mali. Participants were interested in building an understanding of cattle and their production systems for feeding, plowing and dairy and how to manage in a rational way the resources without degrading them and at the same time improve livestock production.

• Model development for an integrated system and land management and water

management program dealing primarily with irrigation systems. Crop models were identified as key tools to help understand irrigation systems and consequences of various management strategies and in use of climate responses and plant responses captured in GIS to help monitor irrigation systems in the region for crop development.

• The establishment of baseline information to support modeling and integrate that

with GIS. Challenge will be to address the issues of fertilization and scaling of land use change. This might be opportunities for IER/ICRISAT/TAMU collaboration.

Objective 2. Review and discussion of current Global Decision Support System (GDSS) models available or in development for use in Mali and West Africa to assess economic impacts of technology or policy options for agriculture Terms of reference: The results presented at the December 1999 workshop reflect the research on model development and use. As noted above, the Mali ACT is one significant and now available deliverable for future collaboration. We have presented the spatially explicit analysis that created geographically explicit simulation zones and the subsequent use of the EPIC model to estimate yields for various input assumptions. The preliminary studies relating use of our forage models and the ACT-EPIC to historical satellite imagery was also presented. We regard these as being steps along the way and look forward to further refinement of these models and data bases in this collaboration. We will review these products and provide updates on progress since the December workshop. We will suggest how these models might be made more interactive within the GDSS and with other models of our collaborators. Results:

• The Almanac Characterization Tool (ACT) is used in the IMPACT process to develop spatial frames and simulation environments to represent the impact of technologies and policy. ACT is a packaged set of geo-referenced data and query tools targeted for use in agricultural and natural resource management activities. The objective


of the ACT is to provide synthesized information to decision makers at the regional or country scale. As an information tool, the ACT supports development investments. The spatial data in the MALI ACT include gridded climate surfaces and modeled surfaces suitable for germplasm adaptation studies, soils, population density, elevation and its derivatives, land cover, and recent census and human nutrition information. These data are combined with infrastructure data (e.g., roads, rivers, towns, political units) in a seamless windows-based application. All information is fully indexed (searchable) textural information is linked in ACT via Adobe Acrobat Reader, allowing the delivery of complete reports on a target area integrated with the spatial data. All analysis conducted in the first 2-years of analysis of the impact of sorghum-millet farming technologies in Mali were integrated into the first release of ACT for Mali.

• The EPIC/APEX crop simulation models were used to predict crop yield and

environmental processes (runoff, erosion, N&P loss, pesticide loading, and others) on croplands. EPIC is a point based or field level model while APEX is a multiple field crop growth and hydrology model for those watersheds where all runoff passes through the site in 24 hours. These biophysical models use characterization of soils, surface conditions, crop management practices, crop growth characteristics, and daily weather to produce crop yields, biomass yields, runoff, erosion, pesticide loss and nutrient (N, P) loss from the cropping ecosystem. Both of biophysical models are capable of modeling mixed crops and relatively simple pastureland systems.

Using the ACT tool, climatic patterns of the region are classified into spatial clusters and FAO soil groups overlain to produce simulation zones driven by spatially coherent long-term historical weather data. A matching, dominant soil pedon is selected from the USDA international pedon database to parameterize the models. Six crops were simulated with a variety of management inputs provided by focus groups in Mali and scientists working with the INTSORMIL and PEANUT CRSP. Area weighted responses of crop yields, soil erosion and runoff were developed for input to the sector and farm level economic models.

• Use of PHYGROW to determine changes in plant production, hydrology and

animal consumption within complex rangeland communities. Environmental processes include runoff, animal competition, and water balance. PHYGROW is a biophysical model, which allows characterization of complex rangeland communities grazed by multiple herbivores, reflecting a given soil type representative of a component in a virtual landscape comprised of multiple plant communities. PHYGROW provides information on plant growth, stocking rates, offspring crops/weaning weights, diet analysis, and full water budgets for hydrology analysis that can be reflected as point, field or landscape level analysis. Output of PHYGROW has been linked to the SWAT basin level hydrology model to link changes in land use and land cover management to hydrologic conditions. PHYGROW was not used in the Mali sorghum-millet technology’s impact assessment but was used for assessment of small holder dairy in East Africa.

• Use of the NUTBAL nutritional balance analyzer to assess performance of cattle,

sheep and goats and determine least cost solutions to mediating hardships of the animal. NUTBAL is a nutritional balance model that accommodates differences in breed types, environmental conditions, forage quality, feed inputs, metabolic modifiers and grazing


pressure. Estimates of gain/loss and likely pregnancy rates can be predicted with the system. NUTBAL was not used in the Mali sorghum-millet technology’s impact assessment but was used for assessment of small holder dairy in East Africa.

• Use of the SWAT river basin hydrology model to predict impact on entire river

basins including streamflow and soil loading. SWAT allows large, river basin scale analysis of streamflow, nutrient loading and pesticide loss. SWAT was not used in the MALI analysis but was used in the East African component of the analysis on impact of small holder dairy technologies.

Objective 3. Identification of areas for collaboration between partners and definition of separate and joint areas of research for collaboration in terms of research objectives and resulting outcomes Terms of reference: This will be one of the most important tasks of this planning session. There are several relatively closely related plans between our groups and a careful examination to find areas of useful intersection is needed. We want to look at GIS activities for multiple applications and would like to see these involve the economics, environmental, and socio-cultural elements of our overall program to develop the GDSS. Results: Participants identified 1) key responses required by multi-level economic models (yield, variation in yield for crops and livestock) – 2) key environmental indicators that reflect critical ecological process affecting long term sustainable production of food (forage, feed, food, livestock) in the Sikasso region – 3) Key issue of determining those processes that we can currently measure, those processes which we need to measure and those processes where we have the personal commitment, personnel and funds to measure processes not currently in our suite of models. Several case studies were considered for impact assessment and exercising the models within the Sikasso region. These were divided into cropland, livestock and rangeland issues:

• Cropland: The cotton producing regions of Sikasso were identified as critical problem areas for agriculture particularly as it pertains to yield decline in the region. The major reasons cited by the participants for this decline were reduced soil N, increased soil acidity, low organic matter content of the soil, alteration of the soil texture, striga infestations forcing abandonment of good lands to marginal lands, shortened fallow times not allowing recovery of soil nutrients, deep leaching of soil N with increasing acidity.

Potential technological interventions for croplands were identified by the participants (legume overseeding, liming, ridging, supplement livestock to get more manure, less acidifying fertilizer formula, soil conservation techniques, composting, kralling of animals, manure management, IPM, improved recommendations on use of mineral fertilizers). Potential constraints to application of the technology impacting adoption are water holding capacity of the soils, land tenure and crop management impacts.


• Livestock Production: Problem areas identified in Sikasso included increase

livestock numbers due to transfer of cattle from the drier regions of the country, low profitability of livestock operations. In the Sikasso region parasites, tsetse and tick borne diseases are critical. Potential technological interventions for livestock production systems identified by the participants included expansion of the dairy sector in peri-urban regions, use of supplements, improved pricing structures, pay by weight instead of head to capture improved weaning weights/ conception rates, improved herd management.

• Rangeland and Woodlands: Problem areas identified by the participants on

adjacent and associated native lands in the Sikasso region included loss of forage species, low availability with fluctuation, forage quality, fuelwood pressure reducing trees. Potential technological interventions for rangeland and woodland ecosystems identified by the participants included infusion of improved pastures to help reduce grazing pressure and improve quality (Glycine, legumes, Andropogon gayanus), deferment strategies, rotational grazing, tree fodders, tree planning to increase wood production and improved techniques, living fences, stonelines for water management, improve fuelwood harvesting methods, village landscape management. Constraints on the success of these technologies depended largely on water holding capacity, land tenure constraints and loss of nutrients in erosion and water runoff.

There was a general consensus by the participants that livestock were viewed as the integration mechanism between landscape systems and modeling systems. The problem formed the foundation for testing the IMPACT methodology of the FIVIMS pilot. The ability to translate the improvement of croplands, improved livestock production systems and enhanced use of native rangeland for human nutrition and reduced environmental consequences were felt to be major issues.

Objective 4: Define explicit experimental design for three main components for extending the current plan of action for the Mali FIVIMS Pilot Study, including participants and time schedule for the segments of collaboration Terms of reference: Based on the above assessment, we hope this planning session will proceed to define explicit areas of collaboration. It will likely be important to maintain dialogue with other work sessions during the workshop as the applications of the methods discussed here will involve all three parts of the workplan. This planning session should consider the outcomes and final products of the collaboration and how they might be organized for best accessibility and use. How will the spatially explicit information be networked for broad accessibility? Are there opportunities for models to feed each other? What kind of packaging should be considered for future utility by analysts in developing countries? Results: First step is to identify the suite of models needed to determine the impact of any major agricultural or natural resource management technology or policy for the Sikasso region. Then, the next step is to develop plans for collection and evaluating existing data and information in a


spatially explicit framework. Finally, it is a matter of identifying who will do what and how and with what level of external funding with specific collaborators, timetable, and interactions defined.

• Experimental design (i.e. chart below)

Impact Assessment Framework

Define Technology/Policy

Define Indicators

Economic Environmental Human Welfare

Geographic Characterization

Assemble & Exercise Biophysical Models

Economic Impact Analysis

Sector Farm level

Conduct Spatial Extrapolation Where Needed

Environmental Impact Analysis

Human Nutrition Impact Analysis

Geographic Characterization of Output

Assess Adoption Rates Spatially

Cap

acity

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• Models to be used will include the full spectrum of biophysical models outlined earlier including EPIC/APEX, PHYGROW, NUTBAL and SWAT.

• The activity tasks to be pursued to support the biophysical and spatial analyses are :

- Spatial Analysis : Consolidation of existing data themes to be included in the creation of the simulation zones for both EPIC/APEX and PHYGROW to provide yield data to support the economic analysis at the sectoral and farm level. Coordination between TAMU, IER and ICRISAT will be required to assure that the correct data themes are loaded and criteria set to establish the simulation zones and the spatial information to support the adoption analysis and human nutrition profiling component of the analysis. For each simulation zone, a virtual landscape will be described in terms of rangeland, cropland and other land. For each land cover class, composition of crops and rangeland ecological sites will be specified.

- Soil Characteristics : For each unique component of the virtual landscape, a modal soil will be assigned from the international pedon database and reviewed by IER and other regional soil specialists and a final parameterization assigned on best knowledge as of the time of submission. The team of IER and other soil specialists will then assign biophysical characteristics of the modal soils associated with site degradation due to extended cropping or grazing environments.

- Crop Management Practices : For each crop and major production zone within

Sikasso, a group of agronomists will review all the management practices files used in EPIC or APEX prior to conducting the simulations.

- Livestock Inventories : Data will be acquired on typical herd structures by kind

and class at the modal village (Farm) level and by political district.

- Livestock Breed Attributes/Inputs : IER animal specialists will assign critical breedtype attributes for the major breeds of cattle and small ruminants (sheep and goats) that will be characterized in NUTBAL.

- Livestock Nutritional Profiling : Because there is limited information on nutritional values of crop residues and rangeland forages, a systematic sampling will be taken for three major regions of Sikasso (dry, mesic, humid) in representative villages selected in coordination with the adoption and economic analysis. Monthly fecal samples will be collected for cattle, sheep and goats and used in the NUTBAL profiles of animal intake and performance. Concentrates used by pastoralists will be analyzed as well for inclusion in the analysis.

- Rangeland Plant Community Characterization : For each of the modal rangeland communities, rangeland ecologists in IER will assign maximum percent cover of the major plant species in the community, assign the normal stocking/movement rules, and preferences for each of the plant species by herbivore for PHYGROW.


- Fuelwood Pressure on Rangeland : Because village expansion and demand for cooking fuel, wood cutting on rangelands/woodlands can significantly alter vegetation composition and hydrology of the landscape. There will be a need to assemble allometry equations available for the major tree species to allow PHYGROW to specify initial wood biomass and changes through time. Equations developed by TAMU and ICRAF will be reviewed along with any equations developed in West Africa (AGHRYMET, INSAH).

- Hydrology Issues : A review of stream gauges will be made and mapped relative

to the Sikasso region to determine the level of watershed response can be pursued. If a large river basin can be defined with sufficient weather and matching stream gauge data, then SWAT will be run on this dataset reflecting current and projected land use change from the ASM sector model.

- Weather Characteristics : A review will be made of existing historical data

relative to the Sikasso region and where appropriate integrate this with the existing weather files assembled for the Sorghum-Millet technology assessment.

• Partners identification and role: The following individuals have agreed to facilitate the acquisition of task-critical information and provide modeling oversight for inputs/output verification.

- Spatial Analysis: Malian Facilitator: Sibiry Traore (ICRISAT/IER), Djaby

Bakary (AGRHYMET), Gray Tappan (EROS). - Soil Characteristics : Malian Facilitator: Oumar Doumbia (IER, Sotuba) - Crop Management Practices : Malian facilitator: Zana Jean-Luc Sanogo (IER

Sikasso) - Livestock Inventories : Malian Facilitator: Moulaye Sangare (IER Sikasso) - Livestock Breed Attributes/Inputs : Malian Facilitator: Mamadou Coulibaly

(Cattle, IER Bamako), Hamidou Nantoume (small ruminants, IER Kayes) - Livestock Nutritional Profiling : Malian Facilitator: Hamidou Nantoume (IER

Kayes) - Rangeland Plant Community Characterization : Malian Facilitator: Meme Togola

(IER Sikasso) - Fuelwood Pressure on Rangeland : Malian Facilitator: Harouna Yossi (IER

Bamako) - Hydrology Issues : Malian Facilitator: Mamadou Simpara - Weather Characteristics : Malian Facilitator :Sibiry Traore (ICRISAT/IER)

• Time-frame :

- August –September 2 000: inventory in the historical data set on the IER modal

farms, CMDT farms and IER/ICRISAT GIS lab- locate secondary data to update to 1999 information and census information - spatial stratification and “geographical equivalents” - Selection of sampling farms: integrate the IER survey with CMDT survey area. Whole region is targeted, minimum of 3 zones – GPS readings.


Session B Agricultural Economic Models and Assessment of Impacts of

The Impact of Technology and Policy Options. Interfacing Models and Building Capacity

- October - November 2 000: Acquisition of data available - confirmation of modal soil biophysical parameters in the models, particularly EPIC/APEX and PHYGROW - identification of crops and rotations, tillage and management practices - defining modal plant communities on rangeland, defining site degradation conditions and reviewing plant growth attributes - Assessment of lacking data - Questionnaire development - pre-testing of the system - explore indicators, status of ecosystem, land degradation - link with satellite / GIS data.

- December 2 000 –January 2 001: Field surveys. Related to the biophysical

models, EPIC crop yield and mixes with their prediction where we do not have modal farms…PHYGROW for other rangeland and NUTBAL for production coefficient for the ASM input. And using the survey data for inputs on the crop producing activities.

- February – May 2 001 : start exercising models - Capacity building - results

- May 2 001 : workshop III

• Integration Issues : Each of the facilitators will coordinate with the coordinator and

regional coordinators, with central points of contact between TAMU and IER Alpha Kergna, Meme Togola, and Hamidou Nantoume.

Co-Chairs: Dr. Nana Lansry, IER Dr. Bobby Eddleman, Texas A&M University Rapporteur: Mr. Alpha Kergna, IER / ECOFIL Participants: To be completed Purpose and Focus of the Planning Session: There are several key next steps in developing the economic component of the Global Decision Support System (GDSS). From the research standpoint, there is the need to continue to refine and make more useful and usable the sector and farm level models. There is need to further integrate these models with the biophysical and environmental models to complete the goal of establishing a holistic approach to impact assessment. There is the intent to undertake specific case studies to answer “real world” questions as a platform for further development of the models. The MDR (CPS) Working Group on policy models is considering the available resources within Mali that can contribute to the overall goal of an improved capacity to assess the status of food


security and vulnerability as well as evaluate technology and policy options for the future. There is the stated intent to establish and use a National Task Force for Food Security Models, which will work across ministries and agencies of the GOM involved in food security monitoring and intervention. Most of the current modeling capacity in Mali is on the economic component. Currently, INSAH and IER, with support of the French Corporation, are adapting the MATA model for farm level economic policy analysis in Mali. The economic models in GDSS, while relatively comprehensive, are complex and, as yet, not well understood by scientists in Mali. The original thinking that led to this planning session was to present these models in more detail than was possible at the December workshop, to provide a forum for discussion and exchange of ideas, and to increase the understanding of colleagues about their structure and use. At the same time, there is need to ensure that we achieve the intent enunciated in the December workshop of developing an overall frame of reference and network in Mali that would allow the total modeling resources available in the country to be accessed and used. The intent is that this will serve as a model for how similar capabilities and capacities would be organized in other Sahelian countries. More specifically, the conclusions of the December workshop and the MRD (CPS) Working Group assume that the Mali FIVIMS Pilot Study will continue to develop the integrated suite of models in the GDSS and that this will serve the GOM as a general framework into which other related capacities can be organized and used. Generalities: The workshop began by self-introduction of participants and their current duties and interests in the modeling of the economic components of the Mali agricultural sector and related subsectors. An agenda and time schedule for topics to be discussed in the workshop was presented to participants by the co-chairs and all participants approved it. The agenda included the four objectives to be achieved by the workshop: Objective 1. Discussion and consensus of underlying economic, biophysical, environmental and socio-cultural factors involved in assessment of impacts of technology and policy options for agricultural production and management of natural resources Terms of reference: Discussion at the December workshop identified areas of need in terms of further acquisition or estimation of information needed as input to sector and farm models. More emphasis on regional and informal markets was suggested. There remain challenges in being able to relate economic models at varying levels of scale. The always-present limitation in quality and quantity of data for economic models must be dealt with. Availability and acquisition of existing information remains challenging. Improving models to make them more useful and usable in developing countries is a serious challenge. At the heart of all of this is the urgent need for capacity building at the national level to enable creative use of models to support key decision-makers. Results:


• Where possible economic models in the GDSS should be made simpler, more easily understood, and useable for impact assessment studies.

• Economic models in the GDSS must be adapted to reality by encompassing “real world”

case studies that demonstrate usability and usefulness for technology and/or policy decisions.

• Economic models in GDSS should be developed with an understanding of the availability,

accessibility, and quality of data required to exercise the models for decision making.

• A priority is to put the models to use for decision-making purposes, since other than for pedagogic purposes an unused model is a useless model.

• Specific economic models must be built to address specific needs at differing levels of

scale (farm or household, subsector, sector, macro) but they should be complementary to each other.

• Different key users of economic models should be involved in model conception and

development in order to make the models more useful and results more acceptable to those making decisions or being impacted by the decisions.

• Human capacity building in terms of long term training, short courses, and workshops

using the models for “real world” economic impact assessments, hardware and software for running the models, and logistics for trainers and trainees should be made available to key users. A capacity building strategy needs to be designed within subregions, regions, nationally and for West Africa.

• Key economic factors involved in technology and/or policy impact assessment include but

are not limited to the following: Pervasiveness and intensity of the technology. How widespread and to what extent the

technology is adopted and what proportion of the sector’s output is affected by the technology. Farmer and family priorities for use of farm income (e.g., for future production, or

withdrawals for family consumption items, health, education, or other uses). Farm level decision-makers’ willingness to accept risk, or the aversion to risk taking

(including price, yield, and institutional uncertainties). Internal (within farm) and external (credit or lending institutions) capital constraints

affecting ability to invest in technologies requiring additional capital. Cultural and conventional wisdom regarding farm production practices and what are

acceptable means of production within the community. Education and experience of farm decision maker and the presence of and contacts

with technical advisors (extension personnel, industry representatives, credit advisors, and other agribusiness advisory personnel).


Objective 2. Review and discussion of current Global Decision Support System (GDSS) models available or in development for use in Mali and West Africa to assess economic impacts of technology or policy options for agriculture Terms of reference: As noted above, it is intended that the current MASM and farm models in the GDSS will be presented and discussed in more detail than was possible at the December workshop. In the same session, the current models and those under development in Mali will be discussed and compared to those in the GDSS. We will look at mechanisms to link Mali models and the GDSS models to provide integrated outputs where appropriate. Results:

• Four economic models were presented with discussion of their structure and applicability to technology or policy impact assessment – Mali Agricultural Sector Model (MASM), Farm Level Income and Policy Simulation/Technology Impact Evaluation System (FLIPSIM/TIES) for farm level economic impact assessments in developing countries, Multi-Level Analysis Tool for the Agricultural Sector (MATA), and the Policy Analysis Matrix (PAM) for assessing national policy options for subsector planning and development, e.g., rice, cotton, cattle, etc.

• MASM is a normative model that maximizes economic welfare subject to regional and

national market balance and resource constraints. It is multisector and multiregional and provides equilibrium solutions to commodity supply and demand intersections in its structure. MASM upon solution generates estimates of agricultural commodity prices and quantities, input use, land use, crop and livestock mixes, and consumer and producer economic surpluses.

• Stochastic versions of MASM include a crop yield distribution and a risk cost in the

objective function to account for yield variability associated with weather. Output, production income, demand and trade therefore depend on the state of nature regarding weather.


Agricultural Sector Model Conceptual Framework

Inputs Model Output

Production Budgets Yields Demand Land Use Multiple Commodities Resource Constraints

Producer and Consumer benefits Prices and Quantities produced Shifts in land use by commodity

Sources of Input

Input To

Almanac Characterization Tool - spatially related data Primary and secondary economic data Crop Yields – EPIC Livestock Performance – PHYGROW and NUTBAL

Agricultural Sector Model National Regional Subregional

Farm Level Models – FLIPSIM, MATA Environmental Models – EPIC – field level SWAT – basin

Almanac Characterization Tool

Spatially Related Input and Output Data and Data Management

• MASM used to assess economic impacts of improved technologies to produce sorghum

and pearl millet developed and tested by collaborative research of Malian and American scientists of the INTSORMIL CRSP.


A 1997 study shows that in Mali, consumers would experience annual economic gains

of 19.7 billion FCFA (29.4 million USD) from the full adoption of the sorghum and pearl millet technologies by producers under 1997 demand conditions. Food expenditures for home consumption by farmers and their families would be

reduced 31.9 billion FCFA (47.6 million USD) annually as a result of full adoption of the improved technologies. Technologies include use of ridge tillage, animal and household manure, and inorganic

fertilizers in combination with improved, higher-yielding sorghum and pearl millet varieties. Two improved sorghum varieties developed by the collaborative IER/INTSORMIL

CRSP program in Mali, N’Tenemissa and Seguetana Cinzana, are food quality and striga resistant varieties adapted to rainfall zones of 600 mm or more, or to areas where guinea-type sorghums are commonly grown. Full adoption of N’Tenemissa and Seguetana Cinzana varieties would provide

additional annual economic benefits to Mali consumers and producers and their families of 6.2 billion FCFA (9.3 million USD) and 5.4 billion FCFA (8.1 million USD) respectively, under 1997 demand conditions. Full adoption of the improved sorghum and millet technologies under demand

conditions associated with population growth to the year 2015 would result in annual economic benefits to consumers and producers and their families of 634.9 billion FCFA (947.6 million USD).

• FLIPSIM/TIES is a whole farm simulation model to capture risk facing small businesses

and for long-term financial planning of the farm business.

• FLIPSIM/TIES combines accounting equations, identities and probability distributions for commodity yields and prices to simulate the financial activities that occur on a farm over a multi-year (up to 10 years) planning horizon.

• Stochastic price and yields as input variables are defined with empirical probability

distributions and pro-forma financial statements are calculated for each set of outcomes that are drawn from these probability distributions.

• These distributions can be analyzed in the context of a base scenario without the improved

technology and current policy conditions and an alternative scenario involving a shock to the system from a change in the technology or policy.

• FLIPSIM/TIES used to access the financial characteristics of three modal (or

representative) farms in Mali – Cinzana farm, Koutiala farm, and Kadiolo farm – associated with adoption of the improved sorghum and millet technologies.

The Cinzana farm had the lowest probability of economic success (i.e., chance of

obtaining a 12.6% or more return on equity) with a 64% chance of being economically successful under current adoption conditions for the improved sorghum and millet technologies.


Non adoption of the two improved sorghum varieties by the Cinzana farm while other farms in the region adopted the technology, reduced the probability of economic success to 24% for the Cinzana farm. Full adoption by the Cinzana farm as well as by all other adopting farms in the region

increased the probability of economic success to 94%. The Koutiala and Kadiolo farms had a 100% probability of successfully obtaining a

12.6% or more return on equity under both current adoption conditions and the full adoption and non adoption conditions for the two improved sorghum varieties. The Koutiala and Kadiolo farms are located in much higher rainfall areas than the

Cinzana farm and both farms produced cotton as a cash crop with a price supported by CMDT. The farm level impact from adopting the two improved sorghum varieties was most

pronounced for the Cinzana farm allowing substantial increase in probability of economic success (from 64% to 94%) and in real net worth (50% to 100%). Non adoption of the improved varieties would be particularly disadvantageous for the

Cinzana farm with much less pronounced impacts on the financial risk of the Koutiala and Kadiolo farms.

• MATA is a descriptive partial equilibrium simulation model developed by the French to

evaluate response trends on agricultural production and food consumption resulting from policy changes.

• MATA assumes farmers’ decision-making process is based on price “adaptive”

expectations that imply there may be a difference between price expected by farmers at planting time and price received after harvest.

• MATA has three components or modules of the agricultural sector

Production module that indicates farmers’ reaction to economic changes and represents

agricultural production through use of modal (representative) farms and a detailed observation of the behavior of each type of modal farm at the regional level. Marketing/consumption module that equilibrates supply from production available for

marketing plus imports with demand from household consumption plus or minus any stocks held for each commodity. Consumers are assumed to maximize utility from purchasing and consuming each commodity subject to a household food budget constraint. Context module of the general macro economic and institutional conditions affecting

the global economy. Parameters include alternative conditions such as input prices, imported food prices, credit conditions, urban household revenue, population growth, etc.

• MATA has not been paramaterized and exercised for the Mali agricultural sector. A

prototype has been developed for Burkina Faso to analyze the effects of the 50% devaluation of the FCFA in 1994 in an attempt to restore export competitiveness, reduce imports and develop the regional economy of countries of the zone Franc in Africa.


• PAM is a descriptive sector simulation model which describes the economic and financial performance of a sector, e.g., rice, cotton, livestock, etc. It provides information of expected impacts from changes in policy parameters used in planning the development of a sector.

• PAM has been applied to the rice sector in Mali with plans to apply the procedure to the

livestock sector in the near future.

Rice subsectors identified based on how water is arranged and managed within a region, the mode of transforming resources and inputs into rice production, and the relative importance of a subsector in contributing to national production of rice. Subsectors producing 2% or more of national production of rice were retained in the

PAM analysis. Sixteen (16) subsectors with systems of irrigation were retained in the Mali rice PAM study. Key parameters examined from 1996/1997 were:

- Agricultural labor salaries (wages) - Nominal interest rate - Real interest rate - Exchange rate - Importation of rice

Benefits from changes in these parameters were found to be 3,295 FCFA (4.92 USD)

per ton of rice at the farm level. Benefits to Mali for the rice sector as a whole were an estimated 1.1 billion FCFA

(1.64 million USD).

• MASM, FLIPSIM/TIES, and MATA use information on crops and livestock production budgets, commodity prices, historical yields, and modal farms to assess sector and farm level impacts of technology or policy changes.

• Coordination of data collection as inputs to these models, identification of modal farms

and associated descriptive statistics, and macro economic variables such as nominal and real interest rates, exchange rates, inflation rates on inputs and commodities, imports and exports of input and commodities are needed in developing and exercising the models.

• The necessity of building a synergy among economic models and between economic, bio-

physical, environmental, and social models is understood and sanctioned to improve decision making regarding technology or policy alternatives.

Objective 3. Identification of areas for collaboration between partners and definition of separate and joint areas of research for collaboration in terms of research objectives and resulting outcomes Terms of reference: Texas A&M has enjoyed a rich collaboration with IER colleagues in the development and evaluation of sector and farm level economic models in Mali and adjacent


countries. We now look forward to extending this collaboration on the food security thrust of current research. The two Malian committees noted above could be focal points for helping focus future joint research needs and approaches. We envision an active continuation of collaboration at both national and sub-national levels as research continues on the development of integrated models using specific case studies as a platform. While a broad interest at the national level continues, we will focus the more intensive integrated modeling effort in the Sikasso region over the next year. In this part of the planning session, we hope that discussion will focus on how we can help each other and how we can make the GDSS more usable. Clearly stated objectives and outcomes will allow us to deal with the next objective in a precise manner. Results:

• MASA, FLIPSIM/TIES and MATA are models that can be applied to case studies in the Sikasso Region.

• The Sikasso Region is recommended as an initial area for pilot case studies, but it is

recommended that the sector models particularly be exercised so as to include other regions of Mali.

• Subsequent studies in the other regions are recommended.

• Choice of model or representative farms for studies in the Sikasso Region should be

jointly done and aggregation of farms within the region and within subareas of the region be harmonized among all models, i.e., economic, environmental, and social models.

• Modelers should list the information required to exercise each model and exchange these

lists, then express ways that will be used to acquire lacking information or data (usually by surveys).

• Current IER/ESPGRN farms (some 86 farms located in 9 villages throughout the Sikasso

Region) and the CMDT farms used in their annual evaluations within and between producing zones need to be analyzed as a starting point for development of modal farms and historical farm level information.

• A complementarily should be developed among economic, biophysical and environmental

models in establishing a spatial framework, designing joint studies, collection of data, and exercising of the models within the same area.

• Three case studies are recommended for consideration as initial pilot studies for

exercising the models within the Sikasso Region. Competition between crop agriculture and livestock in resource usage. Divergence between increase in food production and farm incomes and nutritional

status. Assessment of economic, environmental and social impacts of continued decline in

cotton yields, and impacts of technology and/or policy alternatives to mitigate the effects of cotton yield decline.


Objective 4: Define explicit experimental design for three main components for extending the current plan of action for the Mali FIVIMS Pilot Study, including participants and time schedule for the segments of collaboration Terms of reference: We envision broadening the collaboration with IER’s economic research capacity, engaging additional collaborators at both national and regional levels. In this part of the planning session, we suggest attention be directed to the definition of specific research plans that are based on mutual benefits to ongoing activities and which create new collaboration in areas of mutual need and interest. We would obviously hope that the distinctive areas of expertise of individual collaborators would be used jointly in a complimentary manner. We hope to establish very specific objectives, outcomes, and schedules. A specific plan for packaging models and developing capacity for their use is also needed. The ultimate use of these models in other West African countries should be kept in mind the experimental design is developed. Finally, it remains a first order priority to develop the economic models in concert with other parts of the GDSS so that the holistic assessment capability becomes a reality. Results:

• Models should be exercised with and without technology and/or policy changes to assess the economic, environmental and social impacts of new technology and/or policy components.

• Types of producers and information needs should be identified for each suite of models

and the levels of data collection be specified for exercising each model.

• With existing IER/ESPGRN and CMDT data on size and types of farms, a spatial framework for collecting additional data and exercising the models within the Sikasso Region should be developed.

• Spatially explicit data should be collected that improves existing databases (e.g., IER,

CAE, CPS, CMDT).

• Time frame for reviewing existing farm level information, identifying lacking information and data, designing and pretesting survey instrument(s) and conducting surveys should be established. Economic data should be jointly obtained from any farm surveys with persons

collecting biophysical, environmental, technology adoption and social information. Personnel involved directly in the development of the Sikasso Region MASA and

FLIPSIM/TIES models and their use to examine case studies are: - Alpha KERGNA, IER/ECOFIL - Hamady DJOUARA, ESPGRN/CRRA Sikasso - Bobby Eddleman, TAES, TAMU/Corpus Christi Center

Time frame for sharing and developing information as follows:

- July 15th


Session C Factors Affecting Adoption of New Technology

for Application to Heuristic Rule Making

Eddleman send templates, computer disks and hard copy of data for MASM and FLIPSIM/TIES representative farms to KERGNA.

- July 15th - August 15th

KERGNA and DJOUARA obtain and send information on ESPGRN/CRRA Sikasso farms and CMDT farms to Eddleman.

- August 16th - October 31st

Review of farm level data. Development of modal farms and design of MASM and FLIPSIM/TIES components of farm survey instrument for additional data collection. Selection of real world case studies. Done jointly with all TAMU Impact Assessment Team members and Mali personnel carrying out economic modeling and assessments, KERGNA, DJOUARA and other IER and INSAH personnel. Collection of subregional secondary macro economic data for structuring MASM for the Sikasso Region by KERGNA.

- November 11th - January 31st

Conduct of farm surveys of the modal farms by TAMU, IER, and INSAH personnel yet to be determined. KERGNA and DJOUARA lead collection of economic data for TAMU economic models.

- January 1st - May 1st

Exercise of impact assessment in a sequential fashion to evaluate economic, environmental and social impacts of real world case studies. Plans for IER and other Mali personnel to be involved in exercising the TAMU economic models by short-term (3-4 months) training at Texas A&M.

• Capacity building for Mali counterparts to use the GDSS models is an important

component of next 3 years effort.

• Creation of a network within the sub-regions of Sikasso and nationally for model usage is recommended.

• The National Task Force Committee is recommended to serve as an interface among

network personnel and among developers and users of all models in the GDSS.

• Recommended that a WEB site be developed by Texas A&M that would provide information about the GDSS models and results from exercising the model to examine impacts of previous TAMU and Mali studies and any new case studies.


Co-Chairs: Dr. Oumar Niangado, Foundation Novartis Dr. Neville Clarke, Texas A&M University Rapporteur: Dr. Ramadjita Tabo, ICRISAT

Mamourou Diourte, IER / CRRA Sotuba Participants: 1. Adama Bore DNAMR 2. Neville Clarke Texas A&M University 3. Dalinon Coulibaly DNAMR 4. N’Golo Coulibaly IER / CRRA Sikasso 5. A. Rejane Dembele IER 6. Mamourou Diourte IER / CRRA Sotuba 7. Marcel Galiba Sasakawa Global 2000 8. Oumar Niangado Foundation Novartis 9. Ramadjita Tabo ICRISAT 10. Bino Teme IER Direction Bamako 11. Samba Traore IER / Cinzana Purpose and Focus of the Planning Session: Assessing the economic and environmental impact of a specific technology package requires a realistic estimation of the traditional, current, and maximum future adoption rates that can be expected for the technology. The selection of realistic adoption levels requires careful and methodical consideration of a variety of factors. Socio-economic variables, in particular, often add complex and site specific considerations to decisions regarding the adoption of a technology. In this session, the major emphasis was on addressing the first specific objective. A panel of experts knowledgeable about community and farmer behavior relative to adoption of new technology or responding to changes in policy will be engaged in discussions leading to the identification of the major factors involved as a function of region of the country and other relevant variables. The individual who can provide this form of expert opinion must have an extensive knowledge of producers’ ability to integrate the technology over a range of social and geographic settings. It is important that the experts have a “mental geography” that allows them to define and stratify geographically where the technology can be applied appropriately. This “mental geography” for spatially stratifying where the suite of technologies is appropriate is also important for environmental analysis. When considering the environmental impacts of a technology the “where” question of adoption is critical. Generalities: The workshop began by self-introduction of participants and their current duties and interests on the factors affecting the adoption of new technology. An agenda and time schedule for topics to be discussed in the workshop was presented to participants by the co-chairs and all participants approved it. The agenda included the four objectives to be achieved by the workshop: Objective 1. Discussion and consensus of underlying economic, biophysical, environmental and socio-cultural factors involved in assessment of impacts of


technology and policy options for agricultural production and management of natural resources Terms of reference: This session will deal with the specific factors or variables affecting adoption of technology in Mali and to identify relevant sources of related information. The outcome will provide a basis for further development of realistic assumptions about the adoption rates for use in technology impact assessment. and contribute to the information needed to construct heuristic rule bases as part of the overall GDSS. As a point of departure for the discussion in this session, we would anticipate addressing the following general questions in a relatively open-ended format with more specific questions posed during the course of the discussion as need to provide focus and outcomes 1) The “landscape” of technology adoption in Mali - factors that can be expressed in terms of spatial stratification, 2) Factors affecting adoption and measurement, indicators of adoption, data availability, reliability, needs for field research, 3) Linkage between factors and rule base outline - The verification/validation process, 4) Scale and time integration issues. Results: It is recognized that there are geographically explicit factors that affect adoption of new technology which derive inputs from economic and biophysical models and related environmental interpretations. In addition, there is an array of other factors, including socio-cultural considerations that affect the adoption of new technology, some of which are not so geographically explicit. Economic and environmental models provide precise definition of the factors affecting adoption provides. Estimates of the limits on adoption of technology in turn provide an iterative input to the integrated DSS to constrain or interpret the impact of biophysical and economic consequences of new technology or policy options. A geographic framework is used relate the variables in the DSS to each other. A geographically explicit output adds value and substance to the product of analysis. Spatially defined and linked data and results are needed to establish and maintain these relationships. In addition, there is need to deal with the factors affecting adoption at various levels of scale, ranging from farm and village levels to national and multinational levels. While impact assessments on new technology have been done for many years in Mali and West Africa, fewer studies have been done on adoption of new technology as part of these studies. Even fewer studies have been done to define and quantify the impact of the complex of factors that affect adoption on rates of adoption of new technology. Participants identified some current studies on factors affecting adoption and sources of reports and data from the grey literature, especially in Sikasso, but generally in Mali as listed below:

• Impact study on maize in southern Mali in 1990: IER and its collaborators • Impact assessment on sorghum and millet in Mali in 1996: IER, ICRISAT, etc • 15 years-databases on various crops in southern Mali for 120 UPAs • Studies on animal traction technologies in southern Mali • Studies on APRON Plus technologies


• Adoption studies of technologies generated in Cinzana station: Student from Switzerland; i.e millet/cowpea intercrop in 1:1 ration=low adoption rate

• Adoption studies of technologies promoted by Sasakawa Global 2000 (SG2000) in Mopti, Segou and Koulikoro, in collaboration with INSAH and Michigan State University

• New village level studies will be initiated by ICRISAT and its partners in Mali • Extension services consider adoption rates in their monitoring and evaluation studies

Generally, the workshop participants believe that developing models of factors affecting adoption will be best done using a bottom-up approach, beginning at no higher than village level and including farm level assessment. Food security issue need to be taken up at the microlevel (Village/UPA). Aggregation to larger scales can build on these insights. It was recognized that the assessment of adoption rates and levels would require specific assumptions about the technology involved, the location of application, and the interaction with other factors. Most of the literature on factors affecting adoption deals with studies at the farm or village level. Few studies have attempted to deal with adoption and factors affecting it at higher levels of aggregation. The DSS requires this kind of input when impact assessment is done at subnational, national, and multinational levels of scale. Discussions in the session on factors affecting adoption produced a wide-ranging set of issues and variables that affect the adoption of new technology in Mali and West Africa. The concept of adoption relates to the integration and the ownership of technologies and is time –bound. Factors affecting adoption can be divided into:

o Intrinsic factors: Linked to technologies (performance, meeting the needs of users, value-added, cost of technology, economic value of technology, etc…)

o Extrinsic: Political, socio-economic, institutional, land tenure, cultural, environmental e.g. rainfall, soil fertility…, pest incidence, market, infrastructures/roads, credit, availability and costs of inputs, training, communication, information, extension methodologies, etc.)

A participatory and holistic approach is essential as it enables scientists to take into account the needs of farmers in developing technologies. Objective 2. Review and discussion of current Global Decision Support System (GDSS) models available or in development for use in Mali and West Africa to assess economic impacts of technology or policy options for agriculture Terms of reference: In previous studies in East and West Africa, relatively simple interviews with groups of extension workers, farmers and researchers have been used to derive a group opinion based on general knowledge and intuition about the rate of adoption of new technology as a function of region of the country involved. These gross estimates have been used as a constraint in the sector and farm level models. Recognizing the limitations of this initial procedure, this work session is intended to take the next step towards developing a more comprehensive albeit subjective basis for establishing heuristic rule bases that can be part of the overall GDSS. Results:


Dr. Neville Clarke presented an example of the study done on adoption of dairy farming technology in Kenya. He indicated that there is a need to improve on the method used. Current adoption rates for the dairy production systems were obtained from published survey data from the MOA/KARI/ILRI smallholder dairy project, KARI personnel, and expert opinion of researchers from ILRI and KARI. Expert opinions drawing upon experience from conducting studies of adoption profiles for the animal breed, forage and feeding, and health components of the dairy production systems were provided by these researchers for full adoption rates. Current and full adoption rates are defined as the percentage of herds in each province using the technologies defined by the animal breed/feed/management system alternatives. Current adoption rates represent the existing mix of traditional and improved dairy production systems, and full-adoption rates represent best judgements of the maximum percentages of herds using the improved dairy production systems within 10 to 15 years after wide-scale introduction of the technologies. The specific scenario definitions for each dairy production system and adoption rates for each system and province are shown in the following table. Table: The Definition of Dairy Cattle Technology and Adoption Rates for the Animal Breed/Feed/Management System Alternatives.

Scenarios Allowed Dairy Production Technology Allowed Sources for Feed

Improved Dairy Current Adoption

Zebu-cattle, (1) Cross breed cattle, (2) Dairy breed cattle with semi zero-grazing, (3) Dairy breed cattle with zero-grazing. (4)

Napier grass Maize residue Native grass

Traditional Dairy

Zebu-cattle (1)

Maize residue Native grass

Improved Dairy Full Adoption

Zebu-cattle, (1) Cross breed cattle, (2) Dairy breed cattle with semi zero-grazing, (3) Dairy breed cattle with zero-grazing. (4)

Napier grass Maize residue Native grass

Cattle Breed/ Feeding System* Province

Current Adoption (%) ** Full Adoption (%) **

1 2 3 4 1 2 3 4

Central 5 5 20 70 0 0 20 80

Coast 75 10 10 5 60 15 15 10

Eastern 50 10 20 20 30 15 25 30

Nyanza 75 10 10 5 40 15 20 25


Rift Valley 50 5 15 30 30 10 25 35

Western 80 10 5 5 40 25 10 25

* The proportion of dairy breed/feeding system (1) representing the traditional zebu breed of cattle with grazing

of native grass and feeding of maize residues is allowed to enter the ASM algorithm at 100% with the numbers for the dairy technology systems 2, 3, and 4 constrained to zero percentages for each region under the Traditional Dairy scenario.

** Defined as the percent of total animals in dairy herds using the technologies defined by the animal

breed/feed/management system alternatives. Full adoption represents the maximum percentage of total animals in dairy herds that would use animal breed/feed/management systems 2, 3 and 4.

Objective 3. Identification of areas for collaboration between partners and definition of separate and joint areas of research for collaboration in terms of research objectives and resulting outcomes Terms of reference: Individuals were included in the panel of experts envisioned for this study that are most likely to serve as collaborators in the ensuing research. To the extent possible in this workshop, we will attempt to meet the objective of developing an explicit plan for research. If necessary, further planning will occur after the workshop. Results: To provide a general framework for definition of the impact of adoption rates, DSS development will include development of a heuristic rule base that establishes a set of relationships linking the factors affecting adoption. We envision that the interaction among the components of the DSS will be a fundamental part of the rule base. The specific cases that use this general methodology for impact assessment will necessarily need to be stated in very precise terms as regards the technology to be evaluated and the situations where it is applied. From the discussions of the workshop, a general approach to developing the heuristic rule base for technology adoption emerged. It includes the following sequential steps: 1. The use of expert panels to assist in the development of the survey instruments that will be

used in farm level studies of factors affecting adoption. These panels will be broadly based and should usually involve farmers as participants along with others. Their selection will be based on several factors including the level of scale involved in the assessment (three levels to be considered: farmer, village groups and extension).

2. The farms used to gather information on factors affecting adoption will be carefully selected using a combination of geographically explicit economic, demographic, environmental, biophysical, and socio-cultural factors. This includes consideration of major crop and livestock commodities. GIS methods will be used to define zones of similar characteristics in Sikasso. This will be the basis for defining sampling frames that assist in locating modal farms representative of the simulation zones.


3. The selection of modal farms representing these simulation zones will be done with consideration of the ongoing IER monitoring of farms in Sikasso in their Permanent Monitoring Assessment Program. Initially 120 UPAs were monitored, but this was reduced to 86 UPAs in three zones and 9 villages covered by ESPGRN (Koutiala, Bougouni, and Kadiolo). At the village level, data are available on rainfall, monitoring of prices, market structure, etc.; at the plot level: uses of inputs, production/yield levels, movement of livestock, revenues and expenditures, agricultural products. IER has included recently the determination of adoption rates of new technologies. The intent is to provide intensive assessment of a relative few modal farms with results linked to the more extensive longer duration measurements made in the ongoing IER monitoring.

4. Two or more specific technology assessments will be used as test cases for development of

the DSS using the modal farms. The results of these specific cases studies will be applied to the goal of developing a geographically explicit heuristic rule base will be to have more general application. For example, it might be of interest to understand the reasons for low rates of adoption of new sorghum varieties (10 to 25% depending on the region)

5. The instruments to query farmers in the surveys will include the combination of biophysical,

economic, and socio-cultural factors to be assessed. The modal farm assessments will be done over the period of July 2000 to June 2001.

6. Expert Panels will be used to assist in interpretation of the results of these surveys. There

will be at least partial continuity in membership of the panels involved in designing the questionnaires and evaluating the results.

7. On the basis of the results of these and other studies, the next step will be to develop and

evaluate the heuristic rule base that helps to define factors affecting adoption. The term “heuristic” refers to the method used to establish a set of rules for empirical (observational) factors that determine outcomes. The term also implies a continuing modification of these rules over time until the output represents the perceptions of experts of the “real world”. Thus there will be further need of expert panels to evaluate the products of this process.

8. The rule base for factors affecting adoption will be incorporated into the integrated DSS.

Precise definition of the technology to be assessed and the context in which its application is to be made will make the product of the DSS assessment specific to the situation.– the technology package and the geographically based situation where it is applied.

Objective 4: Define explicit experimental design for three main components for extending the current plan of action for the Mali FIVIMS Pilot Study, including participants and time schedule for the segments of collaboration Terms of reference: The overall plan of work for the Pilot Study involves defining a set of modal farms in the Sikasso region where all the model components of the GDSS will be evaluated together. The general plan is to include an assessment of the factors affecting adoption as part of this total research. The early phase of this new research will be oriented to locating credible sources of information from the grey literature and from experts working in the field. Other


sources of regional and national data on factors affecting adoption such as credit and land tenure will be acquired at the highest level of aggregation that provides credible information. This will be used as a basis for defining the most relevant questions asked at the community and modal farm level. We will attempt to use the data from the more extensive IER monitoring of rural communities in Sikasso to augment the more intensive results from the modal farms. As a result of this work session and travel in the Sikasso region, we expect to identify colleagues in the IER and from relevant NGOs to participate in this study. Results: 1.) Further evaluation of factors affecting adoption with organization and prioritization for research:

• Various organizations such as extension agencies, cooperatives, NGOs, private sector will be consulted in the evaluation of these factors

• Prioritization for research involves the definition of farmers’ s needs and new opportunities.

• There should be a flexibility in the objectives of projects to allow some adjustments to the prevailing farmers’ conditions

• The linkages between research and extension need to be improved • Participatory approach is important • Extrinsic factors seem to be more important than intrinsic ones

2.) Plans for collection and evaluating existing data and information in a spatially explicit framework

• Data are available with various organizations operating in the study area, but they need to be gathered, harmonized, and evaluated. Information from the census carried out by the Ministry of Health on food security and human nutrition will be used and georeferenced by the Texas A&M team

• This can be effectively done by assigning specific tasks to people and by ensuring that all the partners understand what the objectives of the project are and for what these data will be used.

• Data from the communes (derived from the recent decentralization exercise) can be used • Effective collaboration is essential in the collection of data • Each collaborator should be given specific terms of reference • Evaluate amount and quality of available data for use in the models

3.) Definition of specific topics and plans for expert panels

• Expert panels will be used to advise on the initial design of questionnaires • Expert panels will be involved in the evaluation of results. • Ensure that there is an adequate farmers representation in the expert panel

4.) Input from farms monitored by IER (NRM)


• Data from the monitoring and evaluation surveys/activities of IER are available

5.) Linked studies on modal farms for development of integrated models and/or case studies

• Simulation zones are identified using GIS; modal farms are selected and detailed surveys are carried out; Data from IER monitor farms are available

6.) Exploring linkages to the joint IER/ICRISAT GIS laboratory for spatially explicit analysis

• Capitalize on the existing databases in the GIS lab • Integrated economic and NRM information • Exchange of information between staff from the GIS lab and Texas A&M through e-mail

communication • Explore the possibility of assigning a staff from Texas A&M to the lab for a specific

period (medium term) 7.) Initial development of the framework for a heuristic rule base on factors affecting adoption of technology or implanting policy change

• Expert panels (including farmers) help design survey questionnaires to be administered in modal farms

• Assessment of models and results • Refining the model based on the assessments • Heuristic rule base will be developed following the assessment of data by expert panels

8.) Specific collaborators, timetable, and interactions

• IER, Public Health National Research Institute (INRSP), regional services (IER / CRRA Sikasso), Regional Direction for Rural Development (DRAMR), Agricultural Regional Chamber (CRA), Analysis and Development Policy Center (CAFPD), Mission of Decentralization, Regional Direction of Health (DRAS), Regional Direction for Nature Preservation (DRCN), Regional Direction for Planning and Rural Equipment (DRAER), villages organizations, CMDT, CPS, Foundation Novartis, ICRISAT, SG 2000, INSAH, FAO, AGRHYMET, NGOs.

• Short term (next 9 to 12 months): Experiments will be carried out in the Sikasso region • Sharing of resources between the collaborators (human, financial, material) • Long term (next three years and beyond): capacity building ; availability of a

product/model that can be used as a decision support system; case studies will be developed for the practical application of models

• Farmers’needs will be better catered for through the collaboration • Three Cs: Collaboration, Coordination and Communication

As a result of the set of activities to be undertaken as specified above, the timetable for the

period July, 2 000 to May, 2 001 is established jointly with all TAMU Impact Assessment Team members and Mali collaborators as follows:


- July 10 – August 15, 2 000

1. Finalization of the plan of work, the protocol of research and the experimental design with inputs from Workshop II

2. Development of the survey instruments 3. Literature exchange and review 4. Assessment of data needs

- August 15 – November 30, 2 000

1. Exchange list of data required to conduct the analysis with others modelers to come up with a common list of data

2. Acquire information on the ESPGRN and CMDT farms in Sikasso 3. Review of existing farm level data, assess missing data and design common farm

survey instrument for the Sikasso region 4. Spatial framework establishment for selection of modal farms 5. Selection of modal farms 6. Assessment of the experimental design, data needs, modal farms and the

questionnaire 7. Data analysis with data available already in hand to test the experimental design 8. First results

- December 1, 2 000 – January 15, 2 001

1. Expert Panel workshop for adoption experimental design and survey instrument assessment

2. Field survey implementation and data collection - January 16 – May, 2 001

1. Data Analysis : spatial framework development and analysis of farm level data collected in Sikasso Region

2. Rule base development 3. Exercise of impact assessment in a sequential fashion 4. Assessment of results by the expert panel 5. Capacity building in Mali (training…) 6. Mali FIVIMS pilot Study Workshop III

Collaborators involved directly in the development of the Adoption Study in the Sikasso Region are:

- N’Golo Coulibaly, IER/ CRRA Sikasso - Ramadjita Tabo, ICRISAT - Neville Clarke, TAES, TAMU


Plenary Sessions Issues and opportunities Transcending the planning sessions and

Summary Reports and Discussion of Planning Sessions

The workshop was successful in reaching numerous recommendations of the previous workshop, as reflected into the plan of action. Issues and Opportunities Transcending the Individual Planning Sessions This was a session to provide an opportunity for linking the results of the three separate planning sessions and to identify any issues from one session that would have the potential of influencing the outcome of other sessions. This provided an opportunity for dialogue prior to the writing of the individual session reports. Each session rapporteur briefly reviewed the outcome of his/her session and the plenary group provided feedback and discussion. The results of this session are reflected in the reports of the individual sessions. Summary Reports and Discussion of Planning Sessions Rapporteurs presented the results of each of the three planning sessions in some detail and opportunity was provided for general discussion of all participants in the final session. Comments from senior officials of IER and Texas A&M recognized the substantial progress made in formalizing a detailed plan of action for the Sikasso studies. Interactions between groups produced useful insights and conclusions leading toward the final design of the study. A final informal working session following adjournment of the workshop was held the following morning with the scientific leadership of the study to ensure that an integrated approach was clearly established. Commitments for participation in research were made and general schedules for final planning, field studies, analysis, and future workshops were established.

• Further Development of Integrated Impact Assessment Models The workshop has produced a jointly developed perspective on background and issues to be considered in the design of research and has identified collaborators. A relatively few scientists in IER and elsewhere in Mali will have responsibility for follow-up and for ensuring that the agreed agenda is turned into action. The national and regional coordination for the model developments has been given respectively to Mr. Alpha Kergna and Dr. Meme Togola by the Scientific Direction of IER. Plans have been developed for capacity building, including the assignment of IER scientists for long term training at Texas A&M. Products are:

• Agreement on the design of the research project


• National Collaborators agree on data needed to initiate various analyses and develop specific plans for acquiring. These proceed along parallel pathways of biophysical, spatial, and economic data

• Determine Geographic Dimensions of Sikasso Analysis And Establish Sampling Frames

for Selection of Villages and Farms: - Establish simulation zones based on spatial data - Establish locations of representative villages based on spatial sample frame and location of existing villages - Selection and engagement of regional expert Panels or panels to advise on selection of modal Farms and design of survey instruments - Use sampling frames to identify and select modal Farms

• Bringing together the three elements of research background data and information

(economic, biophysical - environmental - factors affecting adoption) and ensuring that the experimental design allows upward aggregation of farm level outcomes and outputs for regional and national ASM

• Final discussion on the actions needed to initiate and conduct the research

• Agreement on tasks and interactions to occur following the meeting

• General plans for Texas A&M and Malian interactions, including additional in-country

activities by the Texas group.

• Discussion and identification of candidate case studies: Cotton yields decline, livestock and environment (including use of GLA), possibly other topics. Seek user identification and authentication.

• Select specific ex ante or ex post interventions to be assessed after baseline models have

been established

• Review and Refine the Experimental Design for Sikasso Studies: - Review and reaffirmation of collaborators and Collaboration, ensuring that schedules and actions are on target, - Experimental Design that ties together the assessment of modal farms in Sikasso with regional and national ASM and creates an integrated approach for modal farm surveys and analysis for biophysical, economic, and socio-cultural data - Define the framework for analysis of Environmental factors affecting the assessment of Methods to enhance sustainable use of natural resources to meet food security needs - Establish methods for linking monitoring of CMDT and IER farms with modal farms survey Data


• Design of survey instrument and validation through use of expert panels and identify enumerators and collaborators at the regional level. Bring together into a single instrument the three elements of the overall assessment of modal farms. Conduct Survey of Modal Farms

- Preliminary design of survey instrument, Prepare surveys to support on farm interviews for the economic analysis (yields, budgets, prices), biophysical analysis (acreage, crops, management practices, livestock inventory, characteristics, practices, rangeland use patterns) and adoption analysis (farm resources e.g. farm size, farmer characteristics e.g. age, gender, education), farming systems, postharvest utilization and markets, farmers' sources of information about new technology) - Evaluation of survey instrument by expert panels, Finalize design and beta test - Conduct Field Surveys on Modal Farms and summarize analysis suitable for representation in the farm level economic models and biophysical models

• Updating and upgrading input data for regional economic models and national ASM and

Preparations for the DHS+ Pilot Study

• Long Term Training for IER scientists at TAMU - Identify Malian collaborators targeted for capacity building - Malian collaborators to TAMU to assist in data analysis and Participate in training

• Analysis of modal farm data, running models for economic, environmental, and societal

outputs at farm, regional and national levels. Putting the pieces together into an integrated analysis

• Review of Results and Regional Workshop on Methodologies

- Preliminary results of analyses reviewed and evaluated by expert panels - Regional Workshop on results and future plans.

Through this next phase of the project, the recommendations on the need for further development of Texas A&M’s capability as described in the draft plan of action with high priority to attach to national capacity building is being reached. The need for further development and simplification to make the models more readily usable and with the participation by both scientists and users of the models during their further development and application is well underway. The collaboration between Texas A&M and IER for development of the models has been expanded to include scientists with expertise in soils, range management, and GIS/spatial analysis.

• National and Regional Institutional Impact The Malian Advisory Committee is active and has provided a number of recommendations to help ensure that realistic assumptions are made, in the next round of scenario evaluations, about farming practices and factors affecting adoption


The best commitment for the future establishment of a National Task Force on Models and Food Security lays in the existing committee organized by the Ministry of Rural Development (MRD) and the Statistics and Planning Unit (CPS). Main objectives of the committee include comparing and contrasting these models and to eventually provide a capacity for determining the most appropriate models for the various tasks at hand. The broad use of models and the demonstration of their utility are part of the goal of this task force. The plate-form of discussions and exchange for models provided by the workshop allowed to further linking Mali and GDSS models, like MATA and MASM. This current committee on models would merge into the National Task Force. A Secretariat has been stated to provide a focal point for the further deliberations of the National Task Force on Models and Food Security. It is expected to have a broad participation in the task force and IER and INSAH are expected to have important convening roles with involvement of MRD/CPS as well as the Ministry of Equipment, the Environment and Urbanism (MEEU) and other elements of the Government of Mali. One of the major products of the National Task Force will be recommendations to the various ministries of government on methods to be used to monitor the status of food security and vulnerability and to evaluate options to meet the World Food Summit goals of reducing hunger by 50% in the year 2015. This major role of the NTF is another step for the development of the suite of models from this pilot study into the broader Mali FIVIMS in relation with the discussions that have been initiated between the FIVIMS Secretariat, UNDP and the GOM about the establishment of a national FIVIMS for Mali. The FAO and other international organizations will advise the government on developing an enhanced capacity for monitoring and analysis. The Texas A&M project is a pilot study for developing models to assist in these objectives under the Food Insecurity and Vulnerability Mapping Information System (FIVIMS). This would promote and facilitate the development of an integrated method for assessment of the status and trends of human nutrition and related methods to improve food security and reduce vulnerability. Results of the workshop is another and promising step for the development of the involvement of regional organizations such as INSAH and AGRHYMET at the outset in the Mali Pilot Study, to ensure a successful transfer of knowledge and capability to other CILSS countries.


Conclusion


List of Participants Siaka Bagayoko Zootechnicien IER / CRRA Sikasso BP 186 Sikasso Mali Tel: (223) 620028 Email: [email protected] Djaby Bakary Agropastoraliste AGRHYMET / CILSS BP 11011 Niamey Niger Tel: (227) 733116 Fax: (227) 732435 Email: [email protected] Abou Berthe Equipe Systeme de Production et Gestion des Ressources Naturelles (ESPGRN) IER / CRRA Sotuba BP 262 Bamako Mali Tel: (223) 242445 Email: [email protected] Adama Bore DNAMR BP 1098 Bamako Mali Tel: (223) 223420 Beau Bush (full address) Texas A&M University Anne Chohin-Kuper INSAH / CILSS BP 1530 Bamako Mali Tel: (223) 220918 Fax: (223) 233479 Email: [email protected]

Neville Clarke(full address) Texas A&M University Dalinon Coulibaly DNAMR BP 1098 Bamako Mali Tel: (223) 222877 Mamadou D. Coulibaly Programme Bovin IER / CRRA Sotuba BP 262 Bamako Mali Tel: (223) 244192 or 242449 Email: [email protected] N’Golo Coulibaly IER / CRRA Sikasso BP 186 Sikasso Mali Tel: (223) 620028 A. Rejane Dembele IER BP 258 Bamako Tel: (223) 215904 Mamourou Diourte Sorghum Program IER / CRRA Sotuba BP 262 Bamako Mali Paul Dyke(full address) Texas A&M University Bobby Eddleman(full address) Texas A&M University Marcel Galiba Sasakawa Global 2000 BPE 3541 Bamako Mali


Tel / Fax: (223) 219028 Email: [email protected] Mamadou Kabirou Coordinator National PSI IER / CRRA Niono BP 73 Niono Mali Tel / Fax: (223) 352049 or 222606 Email: [email protected] Alpha Kergna IER / ECOFIL BP 258 Bamako Mali Tel: (223) 215904 Fax: (223) 223775 Email: [email protected] Geraldine Kouadio FAO BP 1820 Bamako Mali Tel: (223) 223713 Fax: (223) 223646 Email: [email protected] Hamidou Nantoume Programme Petits Ruminants IER / CRRA Kayes BP 281 Kayes Mali Tel: (223) 521662 Fax: (223) 521918 Email: [email protected] Oumar Niangado Foundation Novartis BPE 1449 Bamako Mali Tel / Fax: (223) 241470 Zana Jean-Luc Sanogo Agronome IER / CRRA Sikasso BP 186 Sikasso Mali

Tel: (223) 620028 Fax: (223) 620349 Email: [email protected] Mariam Sow INSAH / CILSS B. P. 1530 Bamako Mali Tel : (223) 22 09 18 Fax : (223) 23 34 79 Email : [email protected] Jerry Stuth(full address) Texas A&M University Ramadjita Tabo ICRISAT BP 320 Bamako Mali Tel: (223) 223375 Fax: (223) 228683 Email: [email protected] Bino Teme IER Direction Bamako BP 258 Bamako Mali Tel: (223) 231905 Fax: (223) 223775 Email: [email protected] Meme Togola IER / CRRA Sikasso BP 16 Sikasso Mali Tel: (223) 7620107 Fax: (223) 620349 Email: [email protected] Bakary Toure Chef du Bureau “Conventions Traites et Accords Internationaux” Domaine de l’Environnemet ME / STP/CIGQE- ATEH BP 2357 Bamako Mali Tel: (223) 231074


Gaoussou Traore Director AGROSOC - PRISAS / INSAH / CILSS B. P. 1530 Bamako Mali Tel : (223) 23 40 67 Fax : (223) 22 59 80 Email : [email protected] Pierre C. Sibiry Traore ICRISAT GIS Manager IER-ICRISAT Regional Modeling and GIS Lab P.O.B. 320 Bamako Mali Tel: (223) 22 33 75 Email [email protected] or [email protected] Samba Traore IER / Cinzana BP 214 Segou Mali Sidibe Yaya DRCN Sikasso BP 38 Sikasso Mali Tel: (223) 621169 To be completed with participants of the plenary sessions and of the economic session


Appendix 1 Provisional Agenda


on Development and Evaluation of Models and Methods

To Improve the Assessment of Status and Estimate the Economic And Environmental Impact of Options to Enhance Food Security

A FIVIMS Pilot Study conducted in the Republic of Mali

July 4-6, 2000 Bamako, Mali

Tuesday July 4, 2000 9:00 AM Convene Workshop

• Welcome by Director General of IER Dr. Alpha S. Maiga

• Report on the National Task Force on Models for Food Security Dr. Bino Teme

• Report of the Technical Advisory Committee for the FIVIMS Pilot Study

Mr. Alpha Kergna

• Objectives and Outcomes of The Second Workshop Dr. Neville Clarke

• Format and Procedures for The Workshop Dr. Neville Clarke 10:30 Coffee and Informal Discussion 11:00 The Almanac Characterization Tool for Mali

Presentation and Discussion of Applications Mr. Beau Bush 12:00 Human Nutrition Data for Overall Food Security

Impact Assessment Geraldine Kouadio 12:30 Lunch and Informal Discussion 14:00 Concurrent Planning Sessions Convene


A. The Use of Remotely Sensed Data, Biophysical Models, and Spatially Explicit Analysis to Assess the Impact on Natural Resources and Environment of Technology and Policy Options Affecting Food Security

B. Agricultural Economic Models and Assessment of the Impact of Technology and Policy Options - Interfacing Models and Building Capacity

C. Factors Affecting Adoption of New Technology for Application to Heuristic Rule

Making

15:30 Coffee Break and Informal Discussion Between Groups 16:00 Concurrent Planning Sessions Reconvene 17:00 Recess Wednesday July 5, 2000 9:00 Concurrent Planning Sessions Reconvene 10:30 Coffee and Informal Discussions 11:00 Concurrent Planning Sessions Reconvene 12:30 Lunch and Informal Discussions 14:00 Concurrent Planning Sessions Reconvene

• Summarize Main Points and Conclusions from Discussions • Define Outcomes Resulting From Collaboration • Finalize Explicit Plans for Collaboration • Define Participants • Establish Schedules

15:30 Coffee and Informal Discussions 16:00 Plenary Session: Progress Reports from Planning Groups - Issues and

Opportunities Transcending the Planning Sessions 17:00 Recess Thursday July 6, 2000 9:00 Concurrent Planning Sessions Reconvene


Discuss and reach consensus on the draft report from the session (prepared overnight by chair, rapporteur, organizer)

10:30 Coffee and Informal Discussion 11:00 Plenary Session: Summary Reports and Discussion of Planning Sessions

1. Report from Work Session A 2. Report from Work Session B 3. Report from Work Session C

12:30 Lunch and Informal Discussion 2:00 Summary of Planning Sessions Continues 3:00 Coffee and Informal Discussion 3:30 Final Synopsis and Future Plans 4:00 Closing Ceremony 4:30 Adjourn

Appendix 2

Announcement of the Second Planning Workshop

On Development and Evaluation of Models and Methods


A FIVIMS Pilot Study Conducted in The Republic of Mali


Co-Sponsors and Host of the Workshop

Co-Sponsors: C Secretariat General de la Presidence de la Republique


C Ministere du Developpement Rural C Ministre de l'Equipement, de l'Aménagement du territoire, de l'Environnement et de

l'Urbanisme C Institut du Sahel C USAID- Mali Mission C United Nations Food and Agriculture Organization C SANREM CRSP - Texas A&M University Host: Institute of Rural Economy Location and Date The Workshop will be held at the Palais des Congres in Bamako during the period July 4-6, 2000. Attendance is by invitation. Background for the Workshop The Food Insecurity and Vulnerability Mapping Information System (FIVIMS) has been established and housed in FAO to monitor progress toward achieving the goals of the World Food Summit. FAO has an interdepartmental working group dealing with progress towards achieving the goals of the Convention to Combat Desertification. FAO also houses the Global Terrestrial Observing System (GTOS) which monitors the status of natural resources on a global scale. The Government of Mali (GOM) is organizing an integrated food security system for Mali and implementing a National Environmental Action Plan for Environment. FAO and the GOM are collaborating to improve the national capacity to monitor and assess the impact of options to improve progress towards achieving the goals of these international conventions. Texas A&M with its collaborators in IER have been developing national and regional models for Mali and adjacent Sahelian countries to assess the impact of policy options and new technology for the last two years. These collaborative studies are being continued under the USAID SANREM CRSP as the Global Decision Support System (GDSS). FAO and Texas A&M plan to further develop and test the utility of these models to aide decision makers in national governments to assess the status food security, evaluate options for interventions to improve food security, and, in doing so, to employ methods that will ensure sustainable use of natural resources. A pilot study (an initial study in one country to develop methods) has been initiated in Mali with the GOM and other partners as an early step in the overall process of development and use of these methods. The results from these studies will be evaluated for use in other developing countries as they strive to meet the goals of the same international conventions, especially the Sahelian countries served by CILSS. To refine the targets and scope of proposed studies, national and regional partners a workshop was held in December 1999 to review, modify, and adopt plans for the pilot study. Participants were asked to discuss their needs for analysis and assessment in these areas. The Texas A&M models were presented and their use discussed. Results from analysis of the impact of sorghum technology on Malian economy and environment was presented as a case study to illustrate the utility of the suite of models. National and regional partners discussed the utility of these


systems and recommended ways in which their utility can be enhanced. Workshop participants included a small cadre of advisors enlisted to participate in the evaluation of results and design of modification of products as the pilot study proceeds. The Worldwide Agricultural Information Center of FAO (WAICENT) is an ongoing participant in pilot study. They are providing partial funding for the workshops. WAICENT has a major role in supporting the FIVIMS Secretariat by providing relevant data bases in an accessible form and methods for assessment of the status of food security and vulnerability at national, regional, and global levels. WAICENT is collaborating with Texas A&M to assess the models and analytic capacity emerging from the development of the global decision support system, using the pilot study in Mali as a “real-world platform” for development and evaluation. The WAICENT data bases and the Knowledge Management Information System (KIMS) were demonstrated during the first workshop. The INSAH major programme on Agro-Socio-Economic Research (AGROSOC) has operational objectives with main activities that will directly benefit from the assessment methods developed being developed by SANREM and FAO in these pilot studies, including the goal of applying lessons learned in Mali to other member States of CILSS. INSAH has therefore agreed to co-sponsor and host the planning workshops and to participate in the ongoing pilot study. This is the second workshop on a collaborative research effort being sponsored by the USAID SANREM CRSP (Texas A&M), the Malian Institute of Rural Economy, and the FAO Worldwide Agricultural Information Center (WAICENT). Objectives of the Workshop The original plan of action for the Pilot Study proposed further development of models through conducting several case studies involving scenarios relevant to planning for food security and natural resource management in Mali. In fact, several of these scenarios were completed in time for presentation at the December 1999 workshop. In considering the recommendations from the first workshop, and interacting with national partners and users, it became clear that additional planning and discussion would help focus the next (more detailed) set of assessments on more specific needs of decision makers and on ensuring that the suite of models are further integrated as the next round of scenarios is undertaken. The process of deliberation with our national partners has continued since the December workshop with two additional substantive engagements in February and May and intervening correspondence by email and telephone. The Malian Technical Advisory Committee has discussed the results of the December workshop and provided a report on their findings. These activities have identified a set of issues and opportunities that will form the basis of in-depth work sessions which will be undertaken at the time of the originally scheduled second workshop in July. However, instead of the second workshop being focused on evaluating the results of impact assessment on several scenarios, it will be more of a research planning engagement. Status reports will be provided on interim activities since the last workshop by national partners, representatives of the Government of Mali and Texas A&M.


The specific objectives of the second planning workshop are to conduct four interactive planning sessions and one plenary session on the status of the pilot study. The planning sessions deal with:

• The Use of Remotely Sensed Data, Biophysical Models, and Spatially Explicit Analysis to Assess the Impact on Natural Resources and Environment of Technology and Policy Options Affecting Food Security

• Agricultural Economic Models and Assessment of the Impact of Technology and Policy

Options - Interfacing Models and Building Capacity

• Factors Affecting Adoption of New Technology for Application to Heuristic Rule Making

• Mali Almanac Characterization Tool: Content, Procedures, Applications The Last Plenary Session is on Status of Implementation of Pilot Study Plans and includes:

• Summary reports and discussion of Planning Sessions

• Report of the Technical Advisory Committee

• Report of the National Task Force on Models for Food Security (Bino Teme)

• Status report on the Mali FIVIMS (CPS and FAO)

• Final Synopsis and Future Plans Format for the Workshop This will be a three-day workshop. The first two and a half days will be for the four planning sessions and will involve national and regional collaborators as well as key operators and managers that will use the methodology being developed and evaluated in the pilot study. The goals and expected outcomes of these work sessions will be described in individual terms of reference and provided separately to participants. The format for the planning sessions will be informal with opportunity for extensive discussion. A key product of these discussions will be definition of the precise goals of the next case studies and of the role of the various partners in conducting and evaluating this research. The last half day will be a session for summarizing the results of the planning sessions and reporting on and discussing the status of various activities involved in the Pilot Study or its implementation.


Appendix 3 Terms of Reference

Concurrent Planning Sessions Second Planning Workshop

on

Development and Evaluation of Models and Methods


A FIVIMS Pilot Study conducted in the Republic of Mali


April 14, 2000

General Terms of Reference for All Planning Sessions Introduction The overall purpose of the second workshop is to engage national and regional partners in further discussion leading to joint development of specific details for implementing the plan of work for the Mali FIVIMS. This will build on the results of the first workshop and two intervening engagements in February and May. Three Planning Sessions will be held in concurrent sessions with plenary sessions at the outset and end of the workshop. There are common general objectives and desired outcomes for the planning sessions. Planning Sessions: A. The Use of Remotely Sensed Data, Biophysical Models, and Spatially Explicit Analysis

to Assess the Impact on Natural Resources and Environment of Technology and Policy Options Affecting Food Security

B. Agricultural Economic Models and Assessment of the Impact of Technology and Policy

Options - Interfacing Models and Building Capacity C. Factors Affecting Adoption of New Technology for Application to Heuristic Rule

Making The plan of action for the Pilot Study involves several components, each of which will be impacted by the planning sessions. These are:


C Further development of the Global Decision Support System (GDSS) models with special emphasis on the integration of economic, environmental, and socio-cultural components into a holistic approach. With current funding constraints, this will involve a focus on the Sikasso region where the aim is to conduct research involving a set of farms representing the commodity, climatic and biophysical diversity of the region. In this research, the data acquisition and analysis will be done concurrently for the three components of the GDSS. The results of this will be combined with the national and regional ASM. Where possible, the goal is to link these studies with ongoing IER monitoring of multiple villages and households in the region and to link inputs and outputs of these studies to the more detailed analysis using the GDSS.

C As part of the development of the GDSS in Sikasso, case studies will be defined in

cooperation with collaborators and users that represent “real world” needs for impact assessment. These case studies will produce a specific set of relevant results. They will also be used as test platforms for the further development of the GDSS. This is consistent with the plan of action emerging from the December workshop.

C Studies relating ground based studies with satellite imagery to assess impacts on livestock

and grazing lands are planned. The objective is to develop improved utility of modern satellite imagery in better defining the status and utility of biomass and to develop improved predictive tools for satellite based agricultural early warning systems. These methods are also aimed at developing improved capacities to assess status and trends of ecosystem health as a result of land use and climate.

Main Objectives for the Three Planning Sessions C Discussion and consensus on the underlying economic, biophysical, environmental, and

socio-cultural factors that are involved in assessment of the impact of technology and policy options for agricultural production and management of natural resources

C Review and discussion of the current GDSS models and related models available or in

development for use in Mali and West Africa. The objective is to develop further understanding (capacity building) and to identify interrelationships between models

C Identification of areas of most useful collaboration between partners and definition of

separate and joint areas of research for collaboration. Define these in terms of research objectives and resulting outcomes.

C Extend the current plan of action for the Mali FIVIMS Pilot Study by defining the

explicit experimental design for the three main components, including the time-phased contributions of each partner. Define the participants and schedule for the segments of the collaboration. Consider the actions needed to define the interrelationship between models and data available or under development in Mali in relation to the GDSS.

Relationships Between Workshop Sessions and Objectives of the Sessions and the Workplan


The cells in the following two matrices contain examples and indicators of the kinds of deliberations requested of members of the three planning sessions. The are only intended to be illustrative and not inclusive.


Relationship Between Workshop Sessions and Objectives of Planning Sessions

Workshop Sessions /

Objectives of Sessions

Use of Remotely Sensed Data, Biophysical Models

and Spatially Explicit Analysis

Agricultural Economic Models - Interfacing Models

and Building Capacity

l Factors Affecting Adoption

of Technology

Underlying factors in impact assessment modeling

Indicators of ecosystem health Local and regional markets, aggregating across scales

Definition of adoption factors by region and situation

Review of current GDSS Models

Preliminary results linking NDVI and RFE rainfall estimates

Further discussion on MASM and FLIPSIM - procedures and outputs.

Currently limited to expert opinions and gross interpretation

Define specific collaborations Relevant data bases and interpretations

Experimental design, research, evaluation

Potential linkages to households and villages currently monitored by IER

Incorporate into revised plan of action

Specific linkages with GIS laboratory -IER/ICRISAT

Field data, interviews, model runs, interpretation

Estimates at regional levels coupled with IER information at village and household level

Relating GDSS to other models and data

CIRAD, ICRISAT, IER and AGRHYMET

Linking Mali and GDSS models - MATA and MASM

Linkages to INSAH, IER, CIRAD and other studies


Relationship Between Workshop Sessions and Plan of Action

Workshop Sessions /

Plan of Action

Use of Remotely Sensed Data, Biophysical Models

and Spatially Explicit Analysis

Agricultural Economic Models - Interfacing Models

and Building Capacity

Factors Affecting Adoption

of Technology

Integrated Model Development

Relating economic models outputs for intensification and extensification with environmental and NRM consequences

Improved interface of biophysical model outputs as inputs to economic models and outputs of economic models to environmental and spatial analysis models

Linking empirical opinion-based heuristic rule base as one component of integrated models for impact assessment

Case Studies as Platforms

Developing input to economic models and evaluating spatially explicit environmental consequences

Specific evaluation of economic options, alternatives, and consequences

Verification of heuristic rule bases in real world situations

Satellite Imagery and Biophysical Models

Linking ground based data and analysis with satellite imagery for enhanced assessment

To be determined

To be determined


Format and Product of the Individual Planning Sessions The individual planning sessions will involve most of two days of the three day workshop. The first half-day will be a plenary session and the last plenary session will commence at 11:00 on the third day and go through the afternoon. Chairs, organizers, and rapporteurs will be identified prior to the meeting. They are encouraged to budget the available time in the session to ensure that the objectives are achieved. The general objectives are provided above and they are further interpreted in the specific terms of reference for each session. Leaders of the session should recognize that each of the objectives identified above are to be considered by their group and addressed in the report from the group. By the end of the second day, each planning session should have discussed and come to agreement in principle on their response to each of the objectives. At the end of the second day, there will be a one hour plenary session in which the three planning sessions will be asked to make a brief (20 minute) presentation on issues and opportunities arising from their deliberations which transcend individual sessions and have potentially broader implications and applications. This will provide opportunity to include these overarching issues as input to the drafting of the reports of individual work sessions After recess on the second day, organizers, chairs, and rapporteurs of the individual planning sessions will be asked to prepare a draft of the conclusions, recommendations, and research plans from the session for discussion by their groups on the following morning. The format of the report should generally follow the list of objectives of the planning sessions. On the morning of the third day, the draft report will be presented by the drafters to the full work session group for discussion leading to a consensus on its content. The final plenary session will begin at 11:00 on the third day. In this session, the report of each planning session will be presented and discussed. Reports on related topics will be included in the final plenary session. An overall synopsis of the workshop will complete the meetings.


Terms of Reference for Planning Session On

The Use of Remotely Sensed Data, Biophysical Models, And Spatially Explicit Analysis to Assess the Impact

On Natural Resources and Environment of Technology And Policy Options Affecting Food Security

April 14, 2000

Purpose and Focus of the Planning Session: This work session is intended to bring together scientists from IER, INSAH, ICRISAT, and TAMU that will collaborate broadly in the areas indicated in the title of the session. It is envisioned that the IER LaboSEP at Sotuba with its multiple collaborators will be one significant focal point for our collaboration. The Texas A&M models and related spatially explicit analysis will be linked with related efforts by our partners to develop an integrated plan of work. We expect the Mali ACT to be a significant existing and available input to further research. As shown in the general terms of reference, we envision the collaboration represented by this work session being involved in all three of the major research components in the plan of action. Our intent is to compare current separate plans for research on agriculture and natural resources which use these tools and define a more meaningful and committed collaboration. At the December 1999 workshop, it was noted that the models which address the environmental component of the holistic approach to impact assessment are not as well defined as those dealing with economic outcomes. This pertains not only to the GDSS, but to the state of science in general in this area. Since the overall goal is to provide a assessment tools that look broadly at the economic, environmental, and societal impacts of technology and policy options, we agreed that the environmental models need to be enhanced and then more effectively integrated into the total Global Decision Support System. With a better definition of these indicators of ecosystem health, it will then be more feasible to undertake case studies using the overall holistic approach. A related but distinct objective in the GDSS work plan is research to improve the utility of modern satellite imagery by relating the primary and secondary data from these sources to relevant ground based information and biophysical models for livestock, forage or rangelands, and crops. The product is intended to be an improved capability for interpretation of satellite imagery applicable to broad areas such as West Africa. If successful, this would improve current assessments of the status and trends in overall ecosystem health for parts of the world which are at risk for environmental degradation. The GDSS approach is to link this more extensive assessment with the predicted impact of new technology or policy options derived from the suite of models under development. Specific Objectives of the Planning Session: C Discussion and consensus on the underlying economic, biophysical, environmental,

and socio-cultural factors that are involved in assessment of the impact of technology and policy options for agricultural production and management of natural resources


Emphasis should be placed on discussing the variables that come into play in an overall assessment of the status of ecosystems at points in time and estimating historical and future trends. These variables should be compared to available information or research underway to provide data which either measure or serve as proxies for these variables. This is part of a larger consultative process with experts from both developed and developing countries. The objective of this part of the session is to define the most important indicators of the health of fragile ecosystems in West Africa, identify the existing information and data for these indicators, and make plans to acquire, assess, spatially represent, and use this information as input to the GDSS. C Review and discussion of the current GDSS models and related models available or

in development for use in Mali and West Africa. The objective is to develop further understanding (capacity building) and to identify interrelationships between models

The results presented at the December 1999 workshop reflect the research on model development and use. As noted above, the Mali ACT is one significant and now available deliverable for future collaboration. We have presented the spatially explicit analysis that created geographically explicit simulation zones and the subsequent use of the EPIC model to estimate yields for various input assumptions. The preliminary studies relating use of our forage models and the ACT-EPIC to historical satellite imagery was also presented. We regard these as being steps along the way and look forward to further refinement of these models and data bases in this collaboration. We will review these products and provide updates on progress since the December workshop. We will suggest how these models might be made more interactive within the GDSS and with other models of our collaborators. C Identification of areas of most useful collaboration between partners and definition

of separate and joint areas of research for collaboration. Define these in terms of research objectives and resulting outcomes.

This will be one of the most important tasks of this planning session. There are several relatively closely related plans between our groups and a careful examination to find areas of useful intersection is needed. We want to look at GIS activities for multiple applications and would like to see these involve the economics, environmental, and socio-cultural elements of our overall program to develop the GDSS. C Extend the current plan of action for the Mali FIVIMS Pilot Study by defining the

explicit experimental design for the three main components, including the time-phased contributions of each partner. Define the participants and schedule for the segments of the collaboration.

Based on the above assessment, we hope this planning session will proceed to define explicit areas of collaboration. It will likely be important to maintain dialogue with other work sessions during the workshop as the applications of the methods discussed here will involve all three parts of the workplan. C Consider the actions needed to define the interrelationship between models and data

available or under development in Mali in relation to the GDSS.


This planning session should consider the outcomes and final products of the collaboration and how they might be organized for best accessibility and use. How will the spatially explicit information be networked for broad accessibility? Are there opportunities for models to feed each other? What kind of packaging should be considered for future utility by analysts in developing countries?


Terms of Reference for Planning Session On

Agricultural Economic Models and Assessment Of the Impact of Technology and Policy Options

Interfacing Models and Building Capacity

April 14, 2000 Purpose and Focus of the Planning Session There are several key next steps in developing the economic component of the GDSS. From the research standpoint, there is the need to continue to refine and make more useful and usable the sector and farm level models. There is need to further integrate these models with the biophysical and environmental models to complete the goal of establishing a holistic approach to impact assessment. There is the intent to undertake specific case studies to answer “real world” questions as a platform for further development of the models. The MDRE (CPS) Working Group on policy models is considering the available resources within Mali that can contribute to the overall goal of an improved capacity to assess the status of food security and vulnerability as well as evaluate technology and policy options for the future. There is the stated intent to establish and use a National Task Force for Food Security Models, which will work across ministries and agencies of the GOM involved in food security monitoring and intervention. Most of the current modeling capacity in Mali is on the economic component. Currently, INSAH and IER, with support of the French Corporation, are adapting the MATA model for farm level economic policy analysis in Mali. The economic models in the Global Decision Support System (GDSS), while relatively comprehensive, are complex and, as yet, not well understood by scientists in Mali. The original thinking that led to this planning session was to present these models in more detail than was possible at the December workshop, to provide a forum for discussion and exchange of ideas, and to increase the understanding of colleagues about their structure and use. At the same time, there is need to ensure that we achieve the intent enunciated in the December workshop of developing an overall frame of reference and network in Mali that would allow the total modeling resources available in the country to be accessed and used. The intent is that this will serve as a model for how similar capabilities and capacities would be organized in other Sahelian countries. More specifically, the conclusions of the December workshop and the MDRE(CPS) Working Group assume that the Mali FIVIMS Pilot Study will continue to develop the integrated suite of models in the GDSS and that this will serve the GOM as a general framework into which other related capacities can be organized and used. Specific Objectives of the Planning Session


C Discussion and consensus on the underlying economic, biophysical, environmental, and socio-cultural factors that are involved in assessment of the impact of technology and policy options for agricultural production and management of natural resources

Discussion at the December workshop identified areas of need in terms of further acquisition or estimation of information needed as input to sector and farm models. More emphasis on regional and informal markets was suggested. There remain challenges in being able to relate economic models at varying levels of scale. The always present limitation in quality and quantity of data for economic models must be dealt with. Availability and acquisition of existing information remains challenging. Improving models to make them more useful and usable in developing countries is a serious challenge. At the heart of all of this is the urgent need for capacity building at the national level to enable creative use of models to support key decision makers. C Review and discussion of the current GDSS models and related models available or


As noted above, it is intended that the current MASM and farm models in the GDSS will be presented and discussed in more detail than was possible at the December workshop. In the same session, the current models and those under development in Mali will be discussed and compared to those in the GDSS. We will look at mechanisms to link Mali models and the GDSS models to provide integrated outputs where appropriate. C Identification of areas of most useful collaboration between partners and definition


Texas A&M has enjoyed a rich collaboration with IER colleagues in the development and evaluation of sector and farm level economic models in Mali and adjacent countries. We now look forward to extending this collaboration on the food security thrust of current research. The two Malian committees noted above could be focal points for helping focus future joint research needs and approaches. We envision an active continuation of collaboration at both national and sub-national levels as research continues on the development of integrated models using specific case studies as a platform. While a broad interest at the national level continues, we will focus the more intensive integrated modeling effort in the Sikasso region over the next year. In this part of the planning session, we hope that discussion will focus on how we can help each other and how we can make the GDSS more usable. Clearly stated objectives and outcomes will allow us to deal with the next objective in a precise manner. C Extend the current plan of action for the Mali FIVIMS Pilot Study by defining the



We envision broadening the collaboration with IER’s economic research capacity, engaging additional collaborators at both national and regional levels. In this part of the planning session, we suggest attention be directed to the definition of specific research plans that are based on mutual benefits to ongoing activities and which create new collaboration in areas of mutual need and interest. We would obviously hope that the distinctive areas of expertise of individual collaborators would be used jointly in a complimentary manner. We hope to establish very specific objectives, outcomes, and schedules. A specific plan for packaging models and developing capacity for their use is also needed. The ultimate use of these models in other West African countries should be kept in mind the experimental design is developed. Finally, it remains a first order priority to develop the economic models in concert with other parts of the GDSS so that the holistic assessment capability becomes a reality.


Terms of Reference for the Planning Session On

Factors Affecting Adoption of New Technology

For Application to Heuristic Rule Making

Purpose and Focus of the Planning Session Assessing the economic and environmental impact of a specific technology package requires a realistic estimation of the traditional, current, and maximum future adoption rates that can be expected for the technology. The selection of realistic adoption levels requires careful and methodical consideration of a variety of factors. Socio-economic variables, in particular, often add complex and site specific considerations to decisions regarding the adoption of a technology. In this session, the major emphasis will be on addressing the first specific objective. A panel of experts knowledgeable about community and farmer behavior relative to adoption of new technology or responding to changes in policy will be engaged in discussions leading to the identification of the major factors involved as a function of region of the country and other relevant variables. The individual who can provide this form of expert opinion must have an extensive knowledge of producers’ ability to integrate the technology over a range of social and geographic settings. It is important that the experts have a “mental geography” that allows them to define and stratify geographically where the technology can be applied appropriately. This “mental geography” for spatially stratifying where the suite of technologies is appropriate is also important for environmental analysis. When considering the environmental impacts of a technology the “where” question of adoption is critical. Specific Objectives of the Planning Session I. Discussion and consensus on the underlying economic, biophysical, environmental,

and socio-cultural factors that are involved in assessment of the impact of technology and policy options for agricultural production and management of natural resources.

This session will deal with the specific factors or variables affecting adoption of technology in Mali and to identify relevant sources of related information. The outcome will provide a basis for further development of realistic assumptions about the adoption rates for use in technology impact assessment. and contribute to the information needed to construct heuristic rule bases as part of the overall GDSS. As a point of departure for the discussion in this session, we would anticipate addressing the following general questions in a relatively open-ended format with more specific questions posed during the course of the discussion as need to provide focus and outcomes:

• The “landscape” of technology adoption in Mali - factors that can be expressed in terms of spatial stratification


• Factors affecting adoption and measurement, indicators of adoption, data availability, reliability, needs for field research

• Linkage between factors and rule base outline - The verification/validation process

• Scale and time integration issues

I. Review and discussion of the current GDSS models and related models available or


In previous studies in East and West Africa, relatively simple interviews with groups of extension workers, farmers and researchers have been used to derive a group opinion based on general knowledge and intuition about the rate of adoption of new technology as a function of region of the country involved. These gross estimates have been used as a constraint in the sector and farm level models. Recognizing the limitations of this initial procedure, this work session is intended to take the next step towards developing a more comprehensive albeit subjective basis for establishing heuristic rule bases that can be part of the overall GDSS. I. Identification of areas of most useful collaboration between partners and definition


We will attempt to include in the panel of experts envisioned for this study individuals that are most likely to serve as collaborators in the ensuing research. To the extent possible in this workshop, we will attempt to meet the objective of developing an explicit plan for research. If necessary, further planning will occur after the workshop. I. Extend the current plan of action for the Mali FIVIMS Pilot Study by defining the


The overall plan of work for the Pilot Study involves defining a set of modal farms in the Sikasso region where all the model components of the GDSS will be evaluated together. The general plan is to include an assessment of the factors affecting adoption as part of this total research. The early phase of this new research will be oriented to locating credible sources of information from the grey literature and from experts working in the field. Other sources of regional and national data on factors affecting adoption such as credit and land tenure will be acquired at the highest level of aggregation that provides credible information. This will be used as a basis for defining the most relevant questions asked at the community and modal farm level. We will attempt to use the data from the more extensive IER monitoring of rural communities in Sikasso to augment the more intensive results from the modal farms. As a result of this work session and travel in the Sikasso region, we expect to identify colleagues in the IER and from relevant NGOs to participate in this study.

development and evaluation of models and methods to ... fivims pilot study workshop ii, july 4-6,...

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