odi Network Paper No.63 _Agricultural Research & Extension Networkj A REN JULY 1996
TOW4R13S MOIIE SUSTAINAJ3LE SOIL FERTILITY MANAGEMEgr- LAUG 24\06 J y Toon Defoer, Salif Kante, Thea Ililhorst and Hugo pe rciot10) GIAOltNi FOuNDATIC5V - AGR;Ctit.TUP.,",!_ FC0i'\10M.
Abstract In southern Mali, more intensive soil fertility motivatesfarmers to plan their own activities. If management strategies are needed to guarantee farmers so request, a field worker assists them to sustainableproduction. However, the increasing implement the new techniques. Village I iversity of the farming systems places high intermediaries are also being trained in mapping demands on research and extension. techniques and practical aspects of the new Technologies pmposed as recipesfor the average technologies. There are clear indications that this fI rmer are becoming less and less relevant. The approach has improved soilfertility management Farming Systems Research team (ESPGRN)o f the practices. Farmers have started to recycle Agricultural Research Institute (IER) nI is considerable amounts of crop residues as litter developing an action-research approach to and fodder. They are also experimenting with enII' farmers, together with researchers, to contour farming and planting fodder crops in I nalyse and understand farmer strategies and association with cereals. practices of soil fertty management and to iI- ntify technologies which both meet farmers' needs and are sustainable. I ER/ESPGRN The authors are part of the Equipe Systemes de Production et The analysis is done at the village andfarm Gestion de Ressources Naturelles(ESPGRN; FSR-team)from the levels, using different participatory tools. First a Centre Regional de Recherche Agronomique (CRRA; the village territory map is made to analyse the Regional Research Centre) of Sikasso, which is part of the mI nagement of the natural resources in the Institut d'Economie Rurale (IER; the Agricultural Research Institute) of Mali. The ESPGRN is a multidisciplinary team of villI.'. Next, the diversity of soil fertility researchers: agronomists, economists, zootechnicians, mI nagement practices between farms is sociologists and land use planners. It is financed by the Dutch investigated and its underlying causes are government and technically assisted by the Royal Tropical Institute (KIT) in Amsterdam. diagnosed. A classification of farms is made by the villagers using their own criteria for IER/ESPGRN distinguishing levels of fertility management. PO Box 186, Sikasso, Mali TO: +223-620028 Fax: +223-620349 Subsequently, the actual management practices Email: [email protected] I- depicted pictorially using resource flow models, drawn by 'test' farmers, representing KIT/AED each of the different categories farms. Mauritskade 63, 1092 AD Amsterdam, The Netherlands of On the Tel: +31 (20) 5688374 Fax: +31 (20) 5688444 II sis of these models, farmers and researchers Email: [email protected] I iscuss various possibilities for increasing the recycling of crop residues and reducing losses The research work on soil fertility management was carried out by IER/ESPGRN in collaboration with the IIED coordinated from theirfarms, and flow models are made to project 'Dynamics of soil fertility management in savanna 1 DI n management practices for the subsequent systems in Africa'. An earlier paper was presented at a year. workshop on Nutrient Cycling and Soil Fertility Management in Africa, 26 November — 2 December, 1995, coordinated by the The combination of analysis and regular Drylands Programme, IIED and hosted by FARM-Africa in feedback of farmers' results, together with Soddo, Welaita, Ethiopia. exposure to information on new technologies,
The Agricultural Research and Extension Network is sponsored by the UKtry_e_rseas Developmendministration (ODA). The opinions expressed in this paper do not necessan y reflect those of ODA. We are happy for this material to be reproduced on a not-for-profit basis. The Network Coordinator would appreciate receiving details of any use of this material in training, research or programme design, implementation or evaluation.
Network Coordinator: Diana Carney Assistant Coordinator: John Farrington Secretary: Alison Saxby
ISSN 0952-2468 Agricultural Research and Extension Network Paper 63
Information from the resource flow models About the authors and their affiliations made by farmers can be transferred into a database which is then used to select Toon Defoer is a Belgian researcher. He has worked since sustainability parameters linked to farmers' key 1992 for KIT as chief technical advisor and agronomist in the criteria of fertility management. These FSR-team of the IER in Sikasso. He has 14 years' experience as an agronomist, extensionist and FSR-scientist in Morocco, sustainabilityparameters allow comparisons to be Comoro Islands, Pakistan and Mali. His major fields of interest made between different categories offarms and are farmer participatory research, natural resource management for the progress of particular farms to be and farming systems research. monitored over time. It is expected that the Salif Kante is a Malian researcher working in the FSR-team of insights gained by using this process about the IER in Sikasso. He has 5 years of field experience with the farmers' decision-making regarding soilfertility FSR-team in the field of agronomy and pedology. management will become relevant for policy- Thea Hilhorst is a Dutch researcher who joined KIT in 1991 makers. after working for 3 years in Honduras with NGOs and farmers' organisations. In 1993 she joined the FSR-team of the IER in Sikasso as a sociologist. Her major fields of interest are natural resource management (especially of common property questions) and client-oriented farming systems research.
Hugo De Groote is a Belgian agricultural economist, working for KIT in the FSR-team of Sikasso. He worked for many years in rural development research in Thailand, Togo and Mali. His current fields of interest include intra-household resource allocation, rural credit, and the quantitative analysis of participatory research.
The authors can be contacted at IER/ESPGRN and KIT.
ii Towards More Sustainable Soil Fertility Management
CONTENTS
Page
Abstract
Acronyms iv
1 Introduction 1
2 The dynamics of the farming systems in southern Mali 2
3 The approach 3 3.1 Diagnosing and analysing farmers' strategies 5 3.2 Planning and implementing system-adapted improvements 6 3.3 Evaluation of the planned activities 6
4 Results from the village of Noyaradougou 7 4.1 Natural resources of the village 7 4.2 Diversity of soil fertility management and farm classification 9 Farmers' criteria 9 Farmers' classffication offarms, according to soilfertility management 9 4.3 Examples of resource flow models 10 Description of a Class HIfarm: a low recyclingfarm 11 Description of a Class Ifarm: a high recyclingfarm 11 4.4 Planning and implementing changes in soil fertility management 11 4.5 Evaluation of planned activities 14 Major achievements 15 Farmers' opinions of the process 15
5 Assessing the impact on the sustainability of the farming systems 15 5.1 Purpose 15 5.2 Data analysis and the development of sustainability parameters 16 5.3 Results 16 Crop residue recycling 20 Production/use of organic fertiliser 20 Dosage of mineralfertiliser 20 5.4 Plans for the future 20
6 Perspectives and challenges 20 6.1 Extension 21 6.2 Research 21
Appendix 1. Organisation of the data files 23
Endnotes 24
References 25
in Agricultural Research and Extension Network Paper 63
Page
Text boxes, figures and tables
Box 1. Extension services in southern Mali 3 Box 2. Agricultural research in Mali 3
Figure 1. Map of Mali, southern Mali, and the cotton belt 1 Figure 2. The action—research approach to soil fertility management 4 Figure 3. Steps in the analytical phase 4 Figure 4. Resource map of village territory made by farmers of Noyaradougou 8 Figure 5. Resource flow model of a Class III farm (low recycling farm) 12 Figure 6. Resource flow model of a Class I farm (high recycling farm) 13 Figure 7. Schematic representation of information flows within the action-research programme 17 Figure 8. Crop residue recycling (kg/ha) 18 Figure 9. Crop residue recycling (kg/TLU) 18 Figure 10. Organic fertiliser utilisation (kg/ha) 19 Figure 11. Manure production per TLU 19
Table 1. Population and land characteristics of southern Mali 2 Table 2. Household characteristics in Noyaradougou 7 Table 3. Criteria for differentiating soil fertility management between farms and underlying socio-economic causes as identified by farmers 9 Table 4. Soil fertility management practices by class of farmer: average and range 10 Table 5. Causes of differences (according to farmers) in soil fertility management practices by class of farmer: average and range 10 Table 6. Equipment, cotton acreage and cotton yield by class of farmer: average and range 11 Table 7. Overview of the major planned activities and principal target groups 14 Table 8. Planned activities that were implemented in 1995 15 Table 9. Users and uses of research results 16 Table 10. Quantities of mineral fertilisers applied (averages by class of farm) 10
ACRONYMS
AV Village association (Association Villageoise) CFDT French Textile Fibre Development Company (Compagnie Francaise pour le Developpement des Fibres Textiles) CIRAD International Centre for Cooperation in Agricultural Research and Development (Centre de Cooperation Internationale en Recherche Agronomique pour le Developpement) CMDT Malian Textile Development Company(Compagnie Maliennepour le Developpement des Textiles) CRRA Regional Research Centre (Centre Regional de Recherche Agronomique) DRSPR Department of Rural Production Systems Research (Department de Recherche sur les Systemes de Production Rurale) ESPGRN FSR-Team (Equipe Systemes de Production et Gestion de Ressources Naturelles) FCFA Franc Zone Currency (Franc de la Communautee Financiere Africaine) FSR Farming Systems Research IER Agricultural Research Institute (Institut d'Economie Rurale) KIT Royal Tropical Institute (Koninklijk Instituut voor de Tropen — Netherlands) PIRL Timber Resources Inventory Project (Projet Inventaire des Ressources Ligneuses) PRA Participatory Rural Appraisal TLU Tropical Livestock Unit ICRISAT International Crop Research Institute for the Semi Arid Tropics
iv Towards More Sustainable Soil Fertility Management
by Toon Defoer, Sail Kante, Thea Hilhorst and Hugo de Groot
1 Introduction and that they neglect social and institutional In southern Mali, fallow periods, which were perspectives (Campbell, 1994; William et al., 1994; traditionally used to reconstitute natural soil fertility, Ming, 1994; Hamilton, 1995). These authors have are becoming increasingly rare (Hoefsloot et al., 1993) called for a paradigm shift in research and extension and the nutrient reserves of the soil are being depleted and a move to actor-oriented approaches which do because of insufficient fertiliser application, a process not view farmers simply as end-users of technologies which is also known as 'soil mining' (Van der Pol, but advocate an active and equitable partnership 1992). The minimum organic matter level which is between farmers, researchers and extensionists needed to protect soils from irreversible degradation (Scoones and Thompson, 1994). Some take the view is actually threatened (Pieri, 1989). The sustainability that researchers and extensionists should primarily act of the farming systems is, therefore, becoming one of as catalysts or facilitators ensuring that information the major issues for research and extension in the and knowledge are openly exchanged (Richards, area. At the same time, however, farming systems and 1994). In all cases authors focus on interactive and soil fertility management practices in southern Mali are collaborative learning, and action-research. Such a becoming increasingly diverse, which makes the task process requires effective tools that assist farmers to of research and extension more difficult; technologies analyse their own management practices and enable proposed as recipes for the 'average' farmer and the them to plan improvements; increasingly these draw 'average' field are likely to become inefficient in this on visualisation of relationships of complex systems context of increasing diversity. (Chambers, 1993; Lightfoot et al., 1992). In order to address complex issues, such as These arguments provide the background to the environmental degradation or soil fertility work being done by the farming systems research management, existing systems concepts, research team (ESPGRN: Equipe Systemes de Production et methodologies, and intervention approaches need to Gestion de Ressources NatureIles) of the Malian be improved upon (Huijsman, 1995). Many authors agricultural research institute (IER: Institut d'Economie argue that present systems approaches rely almost Rurale) in Sikasso to develop a participatory action- exclusively on technical and economic perspectives research approach towards sustainable soil fertility
Figure 1. Map of Mali, southern Mali and the cotton belt
Bougouni LEGEND Koutiala: semi-arid (cotton belt)
--- Isohyet Limit of southern Mali
1111 m Cities 12121EME===1 0 50 10()
1 Agricultural Research and Extension Network Paper 63
farming systems of southern Mali. This is followed by Table 1. Population and land characteristics of an outline of the participatory action-research southern Mali approach and its methodological tools. Next some Sub-humid Semi-arid results from one of the test villages, Noyaradougou, zone zone are presented and the potential for assessing the (South) (North) impact of the action-research on the sustainability of Population density 11-22 13-49 farming systems is analysed. Various parameters for (per km') sustainability, based on quantitative analyses of farmers' own resource models, are developed. The Population growth 0.8 3.5 paper concludes with a discussion Of some of the (% per year) issues that the approach raises for research and Land cultivated 10-20 50-85 extension. (% of arable land) 2 The dynamics of the farming Period of cotton 1980s 1950s systems in southern Mali introduction Agriculture in southern Mali is mainly based on % of cultivated land under 20-25 30-46 rainfed cereal crops such as sorghum, millet and cotton maize, grown in rotation with cotton, the major cash crop. There is one rainy season with yearly rainfall farms which are 79 98 % of ranging from 600 mm to 1,300 mm. The landscape is mechanised gently undulating with drought sensitive, shallow soils of poor fertility in the uplands and more fertile soils (Brons etal., 1994; PIRL, 1989) on the lower slopes and in the lowlands. The area can be classified into 2 zones. The sub- management. The aim of this work is to guide farmers humid zone in the far south is characterised by a in improving and intensifying their soil fertility traditional shifting farming system, with low land use management practices. The approach enables farmers, intensity, long fallow periods and great reliance on together with researchers/extensionists, to analyse and cereals. Cotton was first introduced here 10 to 15 years understand existing strategies, and practices of soil ago. Population pressure and growth rates are fertility management and to identify ways of relatively low, and farming is mostly at subsistence improving or intensifying these (Defoer et al., 1995). level. The approach draws heavily on visual techniques In the semi-arid zone in the north, intensification of developed in the context of participatory rural cotton production, the introduction of animal traction, appraisal (Chambers, 1993) and resource flow and substantial population growth, are transforming modelling as described by Lightfoot et al. (1991). agriculture into a system of permanent cultivation. In The team's emphasis on participatory action- the oldest cotton-producing area (the cotton belt of research does not, however, take away the need to the Koutiala circle), where this process started in the measure the effect of improved management practices 1950s, more than 80% of the arable land is under on the sustainability of farming systems. Indeed, the cultivation and almost all farmers use animal traction success of participatory approaches can only be (Berckmoes et al., 1989). Farmers are also bringing assessed by reference to their effect on environmental shallow, erosion-sensitive upland soils under degradation. Measuring sustainability has generally cultivation. Surplus income from cotton is partly been the domain of hard systems research (through invested in livestock but grazing areas are decreasing, modelling), undertaken in isolation from action- due to the expansion of cultivated land. Consequently, research (Dent, 1995). Brossier and Chia (1994), pressure on communal pastures has been rising, however, show that outputs of farming systems especially at the end of the dry season. With current modelling can be useful in action-research and low-intensity husbandry practices, the carrying Lightfoot et al. (1992) demonstrate that quantifying capacity of the pastures is largely exceeded (Leloup sustainability does not necessarily require formal and Traore, 1989). As a result, the productivity of surveying. Recent efforts are also evolving to link the grassland and livestock is generally low. results of participatory approaches into wider planning Most farmers use fertiliser on cotton. This is made and policy-making processes (Thrupp et al., 1994). possible by the cash income generated by this crop as The participatory resource flow models developed by well as the fact that inputs are supplied on credit by ESPGRN have thus been used to allow the selection of the Cotton Board'(CMDT: Compagnie Malienne pour sustainability indicators and quantitative measurement le Developpement des Textiles). Fertiliser application, ystems sustainability. whether mineral or organic, is however uncommon The paper begins with a brief description of the for cereals, which suffer from a poorly developed
2 Towards More Sustainable Soil Fertility Management
(Defoer and Hilhorst, 1995). Since 1993, the CMDT has Box 1. Extension services in southern Mali been developing an integrated extension approach, Farmers in southern Mali are assisted by the forestry and the livestock services and especially by the Compagnie Malienne which starts with a global village diagnosis, based on pour le Developpement des Textiles (CMDT). CMDT is the participatory rural appraisal (PRA) techniques. The cotton marketing board, a parastatal commercial and industrial approach focuses on human and natural resources and enterprise which enjoys a close partnership with its French analyses the socio-economic and agro-ecological minority shareholder, the CFDT (Compagnie Frangaise pour le conditions of the village(CMDT, 1995). The aim of the Developpement des Fibres Textiles). The CMDT is not only involved in cotton input supply, global village diagnosis is to identify the potential for, extension and marketing but has also been made responsible and constraints to, development at a village level, and by the government, through a contrat plan, for all other to assess overall priorities. Following the global village agricultural extension in southern Mali. The CMDT uses a diagnosis, the idea is to tackle priority problem(s) village level approach to agricultural extension, based on the using a targeted action-research approach. Association Villageoise (AV). About half of the 4,000 villages in southern Mali have an AV, which is run more or less on In response to CMDT's need, the FSR-team in cooperative lines. Through the AV,the village is responsible for southern Mali has been developing specific action- cotton marketing, distribution of agricultural inputs, and research approaches to pasture, livestock and soil management of credit. The AV also has the broad objective of fertility management. All these approaches are village development; it is the entry point for extension interlinked, have a strong systems perspective and messages, both for communal and farm level activities. Functional literacy training and systematic training of farmers attempt to deal with the present challenges in for specific responsibilities within the AV are essential agricultural research and extension, such as the components of CMDT's extension activities. increasing diversity of management practices, sustainability issues and enhancing farmer participation. This paper deals specifically with the marketing system and hence low returns (Berckmoes action-research approach for improving soil fertility et at, 1989).2 management. Agricultural development in southern Mali has not This research programme started in 1993 by only changed the overall production system but has developing and testing methodologies aimed at also increased the degree of difference between farming households. Access to productive resources Box 2. Agricultural research in Mali such as labour, livestock, equipment, quality land and During the mid-1970s, it was recognised that poor interaction knowledge is becoming increasingly differentiated between researchers, extension agents and farmers was the (ESPGRN, 1994). This makes for a large variation in main reason that many technologies which were developed in agricultural management practices and possibilities for Mali were proving to be irrelevant to farmers' needs. In 1979, change. Intensive and extensive farming practices the Institut d'Economie Rurale (IER), the body which is responsible for agricultural research in Mali, decided to create coexist within the same village and even within the an FSR department in order to make agricultural research more same farm household. Kante and Defoer (1994) demand-driven and to address this problem. The activities of showed that farmers'land management practices differ the FSR department began in southern Mali and were supported between fields according to the quality and through collaboration between IER and KIT (the Royal Tropical financed by the Dutch government. topographical position of the land. Institute in Amsterdam), Inspired by the results of the FSR team in southern Mali, 2 During recent years, intra-household conflicts, other FSR teams were established (in 1985 and 1989), and at especially over the distribution of cotton revenues, the end of the 1980s the scope of FSR was broadened from the have become increasingly prominent. Generational farm level to the (inter) village level. conflicts within farm households can make it difficult In 1992, the IER decentralised agricultural research in order increase its client responsiveness. Five Centre Regional de for the household head to mobilise additional, unpaid to Recherche Agronomique(CRRA) were created, with an Equipe labour for tasks such as those directed at improving Systemes de Production et Gestion de Resources Naturelles soil fertility (Vierstra, 1994). Moreover, these conflicts (ESPGRN; ex FSR-team) based at each of them (IER, 1994). The can lead to the splitting-up of the large, extended CRRAs are charged with linking thematic research programmes, families into smaller units. These new units are ESPGRN4 and extension. In 1993 research on natural resource management became the official mandate of the FSR teams. All generally less well-endowed in equipment, terms of FSR teams are grouped into a national research programme on labour and animals. They are also more likely to be Farming Systems and Natural Resource Management, within confined to marginal lands and have less scope for IER. investing in soil fertility maintenance(Van der Pot and Another IER initiative designed to strengthen and Giraudy, 1993). institutionalise farmer participation in defining research programmes, was the establishment in 1994 of one national Faced with these issues of sustainability and and 5 regional Research Users' Commissions. These are diversity, the extension services in southern Mali (i.e. designed to bring users of research into the decision-making the CMDT, see Box 1) have been seeking ways to process about that research at an early stage (Conlon, 1995; ensure that their advice is better targeted and to ESPGRN, 1995). promote a dialogue between farmers and extensionists
3 Agricultural Research and Extension Network Paper 63
Figure 2. Action-research approach to soil fertility management
DIAGNOSIS/ANALYSIS
- Village resources - Diversity of management - Farm level management
PLANNING
- Farmer workshop - Inter-village visits - Farm level planning
EVALUATION EXECUTION
- Village level activities - Follow-up - Farm level activities - Assistance - Progress - Training advice
Figure 3. Steps in the analytical phase
STEP 1 MAPPING NATURAL RESOURCES
STEP 2 ANALYSING THE DIVERSITY OF SOIL FERTILITY MANAGEMENT AMONG FARMS Identifying and prioritising key elements Classifying farms
STEP 3 VISUALISING FARMERS' SOIL FERTILITY MANAGEMENT Resource flow maps
STEP 4 FEEDBACK OF FINDINGS Village meeting: presentation of maps,feedback on techniques Towards More Sustainable Soil Fertility Management
understanding the diversity of existing fertility diversity of fertility management practices at farm management practices with specific groups of farmers level are assessed separately by 3 groups of farmers: (Defoer and Diarra, 1994; ESPGRN, 1994). The results older men, women and younger men. The team may of the programme have been used to assist farmers to suggest this division, but in the end, it is the villagers identify improvements in management(such as better who define the groups. integration of crops and livestock and recycling of In each group, farmers first exchange their views on crop residues) and also to assist researchers and soil fertility and indicators for soil fertility decline. extensionists to target their advice more successfully. Then the major causes of soil fertility decline and In 1994, a monitoring system was set up. One key ways in which farmers cope with this problem are objective of the programme has been to work with the discussed. Subsequently, the issue of diversity amongst extension services to ensure that the methodologies farms is raised and discussed. Farmers' opinions in the developed by the research team are translated into discussions tend to be based on a combination of practical extension tools for the future. local knowledge and information passed on by the extension services. 3 The approach Two lists are drawn up by each group:(1) a list of The action-research approach to soil fertility indicators for good soil fertility management, such as management developed by the farming systems team organic fertiliser production, erosion control and litter (now ESPGRN, see Box 2) has 4 phases:(1) diagnosis use, and (2) a list of socio-economic farm and analysis;(2) planning;(3) implementation and (4) characteristics, such as the availability of labour, cattle evaluation. The whole cycle takes one year. Thereafter and transport facilities which contribute to a farm new activities can be planned, implemented and household's ability to put in place such soil fertility evaluated on a yearly basis (Figure 2). management measures. The lists of the 3 groups of farmers are then amalgamated and prioritised by the 3.1 Diagnosing and analysing farmers' groups; these now become the key criteria for strategies analysis. Next, a single group of well-informed farmers, The analytical phase is conducted by a multi- generally members of the Association Villageoise(see disciplinary team of researchers and extensionists, Box 1), analyses each farm in the village in turn. The using participatory rural appraisal (PRA) tools.3 It name of the household head is written on a card and consists of 4 steps and takes 3 days. Steps 1, 2 and 4 the group then analyses the farm with respect to each take place in village meetings, while the step 3 is of the key criteria identified above. A score is noted implemented at the farm level (Figure 3). on the back of each card to denote the group's view Step 1: Mapping natural resources of the village of whether, or to what extent, the household in The purpose of mapping is to assist with analysis of question engages in the particular fertility management current natural resource use and management at activity listed or has the socio-economic characteristics village level. The village resource map is made by a which are considered important to fertility small group of experienced villagers of both sexes, management. The farmers decide on the level of selected by the village assembly. Indigenous soil preciseness of the values given; in the case of fertiliser types, catena and land use are demarcated.' The use and erosion control, they often use a scale from 1 relative importance of the different types of land use (lowest) to 3 (highest). and reasons for these differences are assessed. A short Finally, a different group of farmers, again selected historic profiles of land occupation is made and all by the village assembly, is invited to classify all farms are then placed on the map. Thereafter, areas of farming households according to their overall level of land degradation are depicted and a discussion is held soil fertility management. Asking farmers to judge their on the causes of the degradation. Then, existing colleagues is a sensitive matter. Experience has shown communal anti-erosion works are demarcated. Finally, that a clear introduction, emphasising that the the map is analysed to identify the constraints and classification will be used to assist farmers in meeting potential for different types of land use (including their diverse needs, is needed to avoid discomfort. both physical aspects such as soil quality and slope The farmers first decide on the number of classes and other issues such as location and marketing that .they will use and how these will be defined. possibilities for produce) and to decide if communal Usually at least 3 categories are used: good, average actions for natural resource management activities and poor. Together the group of farmers decides, should be planned. without looking at the scores already noted on the back of the cards, in which category the household is Step 2: Analysing the diversity ofsoil fertility to be placed. Reasons for the decision are discussed management amongfarms and noted and the card is placed in the appropriate Farmers' criteria for identifying and explaining the stack, name upward. After the classification, the cards
5 Agricultural Research and Extension Network Paper 63 are turned over and the values of the criteria written The team then gives some feedback on concepts and on the cards are compared between farms of the same the technical implications of the suggested class and between classes. Discrepancies are improvements for each class of farms. This intensively discussed. presentation aims to stimulate other farmers who have From each of the classes, at least 2 farms are been placed in the same class as the test farmers to chosen for the next day's farm-level analysis. Ideally consider making similar improvements, taking into these farms have clear differences in scores for key account their own particular circumstances. criteria and also different soil types (taken from their position on the village map). Selection is done by the 3.2 Planning and implementing system- team in consultation with the farmers. Careful adapted improvements selection is important since these farmers, both men After the analytical phase, the test and other interested and women, will eventually become the test farmers. farmers, together with the researcher/extensionist, start During step 2 of the process a number of different planning activities. groups of farmers are consulted (those who draw up Assistance is given to farmers to help them choose the key criteria, those who score households criterion methods to improve their soil fertility and increase by criterion and those who classify overall farm their recycling of crop residues. A farmer workshop, fertility management). This facilitates broad village exchange visits with other villages, and participation involvement in the research and also serves to verify in demonstrations are organised to expose farmers to the information as it is gathered. new technologies. Most of the proposed technologies, (such as contour ploughing, supplemental feeding of Step 3: Visualising farmers'soil fertility livestock and fodder storage) are already in use in management practices other areas. Visits can therefore be made to villages This step is implemented at farm level. After a walk that have been using improved practices for several around the farm fields, members of the test years; experienced farmers demonstrate new households are invited to draw on a large sheet of techniques or tools, and discuss issues such as how to paper the different physical components of their farms obtain the necessary inputs. such as fields, grain and fodder stores, animal pens, At this stage each test farmer makes detailed plans compost pits, etc. Types of soils, acreage, erosion for the following season according to his/her spots and erosion control works are also marked. For production objectives and available resources. Farmers each field, both current and previous crops are noted. prepare a new resource flow model of their farm, a Next, farmers draw arrows to represent resource flows so-called 'planning map', detailing components which between fields and other farm components (such as they intend to instal (such as compost pits, fodder stores etc.). The extent to which last year's crop stores, cattle pens and new fields to be cleared). residues were utilised for different purposes is Intentions regarding such things as crop residue use, estimated and depicted by a pie chart. Then, organic crop rotations, fertiliser application, organic matter use and inorganic fertiliser application on current crops is and feed sources for animals are indicated by arrows. added to the picture as are other resource flows which Proposed levels of resource flow are discussed with originate outside the farm. The arrows are labelled researchers/extensionists, quantified and marked on with the amount of material (and percentage in the the arrows. Field erosion and water control works are case of crop residues), given in local terms and units also noted. The plans made by individual farmers are (cart loads, bundles, baskets, etc.) or in conventional then presented to a further village meeting which is units. followed by discussion of the technical implications of This pictorial record of actual soil fertility executing the changes. management enables farmers to identify, with the team, improvements which are suited to the particular 3.3 Evaluation of the planned activities conditions of their farms. The discussion ends with The planned activities are evaluated a year after the suggestions about ways to increase the recycling of initial analytical phase. An introductory village meeting crop residues to limit losses and to rationalise the use is held and then each test farmer works with the team of external inputs. to assess his/her implementation of planned activities on the basis of the planning map he/she prepared the Step 4: Motivating otherfarmers through presentation previous year. The following major items are offindings discussed: The test farmers from the different fertility classes • fields and crop rotations; present their resource flow models during a village • livestock and farm components (such as compost meeting. The participants at the meeting are invited to pits, cattle pens, etc.); exchange ideas on differences in soil fertility • resources leaving the fields (mainly crop residues); management and improvements that might be made. • resources entering the fields (mainly organic and Towards More Sustainable Soil Fertility Management
mineral fertiliser application); monocropped. Groundnuts are only sown on small • resources entering the livestock and other farm areas. The area under cotton varies considerably components. between the farms, and ranges from 14°A) to more than The resource flows which have been effectively 50°A) of the total cultivated area. implemented are depicted on the planning map and Equipment, livestock and labour is unequally discrepancies between planned and actual flows are distributed among the households. Eighty per cent of discussed. Improvements in management practices can the households own an ox-plough, and about 70% of be demonstrated by comparison with the initial all households also possess other cattle. Goat and resource flow map. sheep keeping is quite common in Noyaradougou. After the individual evaluations with the test farmers, the findings are discussed with other farmers 4.1 Natural resources of the village who were placed in the same category(good, average During the village mapping exercise, farmers in and poor soil fertility management). This helps to Noyaradougou distinguished 5 territory units and 5 highlight the class-specific socio-economic constraints indigenous soil types (local classification of soils is which different households face in implementing based on a set of criteria such as topography, improved soil fertility management practices. The stoniness, texture and colour (Kante and Defoer, evaluation exercise is concluded by a general village 1994).6 These were ranked according to size (see meeting in which farmers of the 3 classes report their Figure 4). findings. Land use differs substantially between the territory units and between soil types. Gravel soils were 4 Results from the village of intensively exploited in the past, but have now Noyaradougou become less attractive as their productivity has fallen Noyaradougou is located in the administrative region and mechanisation has become more widespread. of Sikasso. Its climate is North-Guinean, dominated by Nowadays, the more loamy soils are preferred for one rainy season, and yearly rainfall is about 1,000 cultivation. Women have their own fields close to the mm. Oxisots (ferruginous soils) are the major soil village, almost exclusively on waterlogged, shallow types of the lowland, while litbosols are mainly found soils. They use these to grow cocoyams and rice. on the uplands. The village has approximately 310 Grazing intensity differs between the various territory inhabitants, belonging to 4 lineages, and living in 29 units. Those units with an abundance of fallow land households.5 Two lineages belong to the Senoufo ethnic group, one is Bambara and one is Gana. All households are Muslim. The number of household Table 2. Household characteristics in members differs substantially between the households, Noyaradougou (N = 29) as does the area of cultivated land,and fallow for each Average Maximum Minimum household (Table 2). Land is allocated by the lineage which first settled in the area, although usufruct rights Number of have now become more or less permanent. household 10.7 27 3 members Upon the death of the household elder, families in Noyaradougou sub-divide. Each son creates a new Number of 6.5 15 3 household and the family land is redistributed. During active members recent years, however, households have often split up Area cultivated 8.2 14.5 3.6 before the death of the elder, due to intra-household (ha) conflicts. The newly-formed households are generally Area fallow 7.5 14 3 small and confined to more marginal land. (ha) Pastures and woodland are common property and grazing on both fallow land and crop residues left in % of land 38 53 14 under cotton the field after the harvest is open to all. The livestock system in Noyaradougou is based on cattle that graze Number of 3.5 16 0 on common pastures during the day (for 8 to 10 large livestock hours) and return to a pen, near the village, in the Number of 3.7 10 0 evening. Grazing is mainly on fallow land, near the oxen cultivated fields, during the wet season and on crop Amount of 3.7 7 0 residues left in the fields, shortly after the harvest. animal traction The major crop rotations are cotton-cereal or equipment* cotton-cereal-cereal, with maize being the most important cereal. Maize is often intercropped with * Animal traction equipment consists of: plough, cultivator, seeder millet and cowpeas, and millet and sorghum are also arid cart.
7 Agricultural Research and Extension Network Paper 63
Figure 4. Resource map of village territory made by farmers of Noyaradougou
NOYARADUGU DUGU JAA
Dugu (Village) Ku lu(Colline) —.--.— Kungoda don __—___ Dugukolo suguya (Limite sous_terroir) don/ Limite typede) 1 terre Dugukolo fin 100 01 BE LE (Gravillon)----- Ji sira (Exutoire) (Terre noire) E3 - rili?,ti.- r ,CL.D5 C EncEn (Sable) ---1 Fug a(Plateau) ------> Dugu sira (Route) Qa is.5
Agricultural fields Territory unit Fallow Pasture Woodland Men Women
Nussigue 24 0 10 2 2
Sunturugu 24 , 5 5 1 0
Moroniere 4 4 15 10 4
Faraka 1 1 1 5 0
Nangapirikan 2 2 7 1 1
Figures indicate the relative importance made through ranking (with stones): 0 means that a certain type of land use does not exist at this territory unit. Increasing numbers denote increase importance.
8 Towards More Sustainable Soil Fertility Management
and grasses can be intensively grazed, while units with managerial capacity of the household head. It is creeks are important for livestock during the dry important to be able to motivate the household season. members by setting an example as well as by Land degradation is especially severe in the remunerating all members correctly and equally, intensively undulating territory units. The villagers without favouritism. A good internal household recognise the need for erosion control works to structure, including harmonious division of labour, is protect these zones. of utmost importance for assuring efficient communication between the household members. 4.2 Diversity ofsoil fertility management Large, extended families seem to have the greatest andfarm classification problems in maintaining efficient communication and FARMERS' CRITERIA avoiding friction between household members. Farmers were asked to identify the factors which Farmers identify training courses organised by the explain differences in soil fertility management extension service(CMDT), their own experimentation between households. The factors which they with new technologies and exchanges- with other mentioned related mostly to crop residue recycling farmers as ways to increase their knowledge. and crop-livestock integration. Good managers are Another factor affecting soil fertility management is distinguished from poor managers primarily by the the economic environment. Cotton enjoys stable and types and amounts of organic fertiliser they produce relatively high prices, as well as credit and mineral and the amount of crop residue used as fodder in fertiliser supply facilities and is therefore grown in a cattle pens. Farmers also mentioned the extent of relatively more intensive system. Cereals on the other implementation of anti-erosion measures and the hand have poorly developed markets, relatively low application of recommended mineral fertiliser doses as and uncertain prices and are produced in a less distinguishing features (Table 3). There were few intensive way.' differences between the 3 groups of farmers (older It should be noted that differences in production men, women, younger men) which were consulted goals between farming household were not mentioned about these key criteria. as influencing soil fertility management. Several underlying causes for these differences in Farm households were subsequently 'scored' for management were listed by the groups. Access to each of the key criteria. productive resources such as active household members, catle and carts were considered key. The FARMERS' CLASSIFICATION OF FARMS, ACCORDING TO SOIL groups also indicated that farmers are likely to put FERTILITY MANAGEMENT more emphasis on manure production if they have A different group of well-informed farmers was asked little fallow land or low quality, erosion-sensitive soils. to classify all village households according to overall Knowledge, courage, and the household organisation soil fertility management practices. The results of this and decision-making structure are also important for classification and the way in which it compared to the the way farmers manage soil fertility. However, these scores given for the key criteria in the previous step, factors are difficult to define. Courage or 'drive' of the are given in Tables 4 and 5). active household members seems to depend on the The quantitative analysis clearly supports the differences in management practices that farmers perceived between the 3 classes. Organic manure and Table 3. Criteria for differentiating soil fertility compost production, litter use and erosion control are management between farms and underlying socio- substantially higher for farms of Class I, compared to economic causes as identified by farmers Classes II and III (Table 4). Use of the recommended mineral fertiliser dose on cotton, which farmers also Criteria for differentiating Underlying causes of soil fertility management differences mentioned as a key criterion, does not, however,seem to differ substantially between the 3 classes. • organic matter • cattle ownership The opinions of farmers, both men and women, production • number of active family thus proved to be very consistent, despite differences • litter use in pens members • anti-erosion measures • cart ownership in the way in which these opinions were courted. • recommended fertiliser • amount of land available Farmers are aware of the management strategies of dose to fallow their colleagues and are able to point out the major • type(s) of soils differences. One reason for this might be that the • courage practices identified are visible (cattle pens, compost • knowledge • household organisation pits etc. are all situated near the village), with the and decision structure exception of the dose of mineral fertiliser applied. • amount of cotton grown Table 5 shows the way in which access to resources (and related input use) differs between the 3 classes of farms. Class I farmers
9 Agricultural Research and Extension Network Paper 63
Data on other farm characteristics, such as number Table 4. Soil fertility management practices by of ploughs and oxen cultivators, cotton acreage and class of farmers: average and range yield, was obtained from the Association Villageoise. Class I Class II Class I This showed significant differences between the 'Good' Average' 'Poor' classes of farms (see Table 6). These measures can be considered as an overall proxy for the availability of Organic manure 3 0.7 0.3 production' (3-3) (0-3) (0-2) resources, some of which may be invested in soil fertility management within a household. Bigger farms Litter use' 3 0.8 0.4 also receive more attention from the extension (3-3) (0-1) (0-1) services and may therefore be more aware of the Erosion control' 3 2 1.3 importance of soil fertility management. (3-3) (0-3) (0-3)
Mineral fertiliser 1 1 0.8 4.3 Examples of resourceflow models dose applied" (1-1) (1-1) (0-1) Resource flow models drawn by test farmers were used to analyse soil fertility management practices and N _ 8 6 10 to identify adapted improvements at farm level.
NB: Figures are averages from values attributed to farms for Table 5. Causes of differences (according to minimum and maximum values are found each class: farmers) in soil fertility management practices by between brackets. a Scale from 0-3 class of farmers: average and range b 1 = dose applied; 0 = dose not applied Class I Class II Class I 'Good' Average' 'Poor' have the highest number of cattle, family labour Number of 14.6 11.6 3.4 availability and acreage. Some farmers in Class III, on cattle' (8-25) (4-20) (0-8) the other hand, do not have a cart, which limits their Number of 9.3 6.8 4.2 to return ability to transport residues for recycling and family (7-20) (5-15) (3-6) organic matter to their fields. The acreage of fallow labourers" land does not differ substantially between the farm Area cultivated 10.7 8.4 6.8 classes but the acreage cultivated per unit of family (ha) (8-13) (6-9) (4-8) labour in Class III is considerably higher than for the • other classes. It seems that a high land/family labour Fallow (%)C 57% 69% 69% ratio does not allow for satisfactory crop maintenance (4-14) (3-7) (3-6) and fertility management. Factors such as knowledge, Number of carts 1.2 1 0.8 motivation and courage also differ slightly between (1-2) (1-1) (0-1) the farm classes; all farms of Class I score highly for Couraged 1 0.8 0.8 courage and knowledge. (1-1) (0-1) (0-1) Soil type, which farmers mentioned as being important to fertility management, does not seem to Knowledge' 1 0.8 0.7 (1-1) (0-1) (0-1) differ between the classes. However, since each , , farmer cultivates areas with different soil types, this Land/family 1.1 1.2 1.6 labourer (ha) criterion may not account for differences between , farms, but rather between fields within farms (Kante N 8 6 10 and Defoer, 1994). Comparing farmers within Class I shows that the NB: Figures are averages from values attributed to farms for best ones have neither the most livestock, nor more each class. Figures between brackets are minimum and been shown elsewhere maximum values. family labour. Indeed, it has a that farms with high livestock numbers'have a lower Including oxen • Maximum family labour here is 20, compared to 15 intensity of night-penning and are therefore less in Table 2; this is due to the recent split-up of some of effective in producing manure, than farms with less the large families (not included in the classification, livestock (Vries and Prost, 1994). It is also possible where n =24) that in the larger farms (with more family labour) the • Percentage of land under fallow decision-making process becomes so complicated that For courage 1 = Farmer judged as having a lot of courage to invest in soil fertility management. it hinders the introduction of new technologies. If this • For knowledge: 1 = Farmer having received functional were true it would mean that increases in family education or a training course on agricultural labour are beneficial up to a certain point but there- practices or having many years experience of after are likely to be detrimental to fertility management. 'improved' practices; 0 = No courage and no knowledge.
10 Towards More Sustainable Soil Fertility Management
Table 6. Equipment, cotton acreage and cotton the form of cattle dung when animals graze on yield by class of farmers: average and range common land.
Class I Class II Class I DESCRIPTION OF A CLASS I FARM: A HIGH RECYCLING FARM 'Good' 'Average' 'Poor' (FIGURE 6) This household includes 6 active workers. The farm Number of 1.8 1.3 1.0 ploughs consists of one big field, split up into 12 cultivated plots and one fallow part. Cotton represents about Number of 1.4 1.3 1.0 50% of the cultivated area. It is grown in rotation with cultivators cereals and legumes, such as cowpeas and Number of 7.1 5.0 2.4 groundnuts. Cattle equivalent to 13 TLUs are kept in oxen the same system as the Class III farm (grazing crop Cotton acreage 4.8 3.8 1.4 residues, common land or fallow according to the (ha) season). Recycling of resources between farm components Cotton yield 1.6 1.3 0.8 (tonnes/ha) is quite intensive. All cotton residues (60 carts) are used as pen litter for the livestock. Most legume hay N 8 6 10 (3 carts of cowpea and 6 carts of groundnut) and a small part of the cereal stalks(6 carts from 0.5 ha) are NB: Figures are averages from data obtained from the village transported and used as fodder at the end of the dry database, for each class season. Animals, in this case mostly the household's own animals, eat approximately 20°A) of the cereal Twelve test farmers (representing half the households stalks after harvest. in this small village) were selected from the 3 farm Four sources of organic fertiliser production are classes: 5 from Class I, 2 from Class II and 5 from used: waste from grain-pounding is added to the Class III. Two examples of resource flow models are household waste heap; compost is made mainly from presented here: one of Class III (a low recycling farm) grasses cut from common pastures decomposed in a and one of Class I (a high recycling farm).8 pit; manure from the small ruminant pen enters the compost pit or waste heap before being applied to the DESCRIPTION OF A CLASS III FARM: A LOW RECYCLING FARM fields; and manure from the cattle pen (30 carts) is There are 3 active workers in the household. The farm used exclusively on cotton fields, often concentrated consists of both distant and nearby fields. Cotton- on the poorer and more degraded parts. cereals rotation is dominant and legumes are rarely Resources enter the farm mostly as mineral found. Cattle equivalent to 3 Tropical Livestock Units fertilisers and feed concentrates. Cotton, being the (TLU)graze either on crop residues, on common land main cash crop, receives the recommended mineral or on fallow, according to the season.9 fertiliser dose, while cereals are under-fertilised. Cattle Recycling of resources is quite low. An estimated grazing on common pastures, combined with night- 20°A) to 30°A) of total cereal stalks and about 15% of the penning, represent an input of village resources to the total cotton residues are taken up through grazing and farm. However, valuable cattle dung is lost from the then partly transformed into manure, which is left in farm as animals graze outside its boundaries. Another the field. The rest of the residues are not used. Two transfer of village resources to the farm takes place as sources of organic fertiliser production are used: waste grasses from common pastures enter the compost pit from pounding cereals and small amounts of animal and are used as litter in the cattle pen. Cotton is the manure (25 hired carts). Since the household has no principal product to leave the farm. Erosion is a cart, distant fields are rarely manured. source of resource loss, as is the burning of almost Mineral fertilisers, applied to cotton, are the major half of the sorghum and millet stalks. source of nutrients entering the farm; cereals receive small amounts of fertiliser. Other external resources 4.4 Planning and implementing changes entering the farm include: cotton seed cake, used as in soilfertility management animal feed at the end of the hot season; grazing and Following a farmer workship, exchange visits with night penning on common pastures; and the cutting of other villages and demonstrations of new techniques, grasses from common pastures to be used as litter in each individual 'test' farmer made a new resource flow the livestock pens. Cotton fibre is the principal model, detailing his/her plans for improvements in soil product to leave the farm. Burning of cereal stalks fertility management practices. These planning maps (which account for 40% to 75% of the total residue were then discussed in a village meeting in produced) represents an important loss of organic Noyaradougou. Table 7 shows the way in which the matter. Resources are also lost through erosion and in planned changes differed between the classes of
11 Agricultural Research and Extension Network Paper 63
Figure 5. Resource flow model of a Class Ill farm (low recycling farm)
ao_Lav tO Pasture 'C1--7 Burning Organic manure FarnLEGEND Litter use psmenta — Fodder use El Goat pen Urea 00 Poultry house - Cotton fertiliser fl Grain store - Cereal fertiliser A Waste heap Animal feed 0 Compost pit Crops Waste 1 Maize • Sorghum Other I Millet — Salts Cotton — Dikes 9 Fallow x. 3, Stone lines
12 Towards More Sustainable Soil Fertility Management
Figure 6. Resource flow model of a Class I farm (high recycling farm)
3 4 4 `r,i e Q,5 1 • ' -11.s • .• 4 ha
ilh a ,61( Tha
50*/.
Flows 0 Pasture fe Burning Organic manure • LEGEND - Litter use Farm - -> Fodder use A-- Components CI Goat pen Urea Q Poultry house - Cotton fertiliser • Grain store ...... -.>Cereal fertiliser A Waste heap - Animal feed O Compost pit ..r."roGrasses Crops Waste Maize i" Sorghum Other t Millet - Salts Cotton Dikes L50 çs Fallow Stone lines v Orchard /1g/ Soil erosion
13 Agricultural Research and Extension Network Paper 63
Table 7. Overview of the major planned activities and principal target groups .. 1 CONSTRAINTS ACTIONS PLANNED TARGET CLASS OF FARMS Class I Class II Class III All Farms * * Burning of crop residues • increase crop residue recycling . . . . Little organic fertiliser • use cotton stalks as litter * * , • keep more cattle * • little manure * * • poor compost quality • compost more • add rock phosphate * . , . , Transport • obtain a cart * • compost near fields * * • build cattle pen near fields . i Feed • use cereal stalks as fodder * * • use chaff cutter * * • use nitrogen supplement * * • increase storage before grazing * * • introduce fodder crop: maize/ * * dolichos , ' * Erosion • introduce contour farming
Farmers outside the target class are not precluded from implementing these changes.
farms, to reflect their different underlying socio- Erosion control techniques are more field specific spots economic characteristics. than farm, or class of farm, specific. Erosion and Farmers belonging to Class III (poor soil fertility were indicated on the initial resource maps management), planned to recycle more cotton stalks several farmers planned to install contour bunds uphill to for animal litter. Their small herds limit their scope for from their fields and to practice contour farming manure production, therefore they planned to increase help reduce erosion. organic fertilisation through composting. Because they Farmers were assisted in implementing the new do not own carts, crop residues have to be composted techniques by an agricultural technician from ESPGRN. near their fields. They planned to add rock Demonstrations on fodder storage, chaff-cutting, phosphate'to these residues to increase the quality of supplemental feeding, contour line staking, contour their compost." ploughing, composting and maize/Dolichos lablab -cutter for communal Class I farmers already recycle a fairly high intercropping were given. A chaff small inputs such as proportion of their crop residues for litter. Their main use was supplied on credit and free of charge. focus for improvement was on increased recycling of Dolichos lablab seed were supplied by for the cereal stalks for fodder. Their plan was to remove the The level of assistance provided ESPGRN did not differ stalks from the fields before free grazing, then to store implementation of new techniques that a CMDT extension them (new storage facilities were planned) and feed substantially from the services them to their animals during the fodder shortage agent might provide. period towards the end of the dry seaon. To reduce the need for storage space, and to improve the quality 4.5 Evaluation ofplanned activities of the fodder, they planned to chop the stalks with a Comparison between the test farmers' planning maps chaff-cutter and to add a nitrogen supplement(which and actual implementation shows that many they can make themselves from salt, rock phosphate, improvements in soil fertility management were made molasses, cereal bran and urea). Class I farmers also within a year of the initial analysis. During the planned to increase production of fodder crops in evaluation sessions, most farmers said they were now association with cereals (for example Dolichos lablab burning less of their crop residue, and were using intercropped with maize). more residue for litter, fodder and composting. Such One important constraint identified by these farmers improvements were not limited to the 12 test farmers, was the time taken to transport residues and manure but extended to other farmers in the village as well. between their fields and their cattle pen (near the A number of farmers were not, however, able to household). However, proposals to relocate pens realise their goals. First, an outbreak of various nearer to the fields met with concerns over theft of livestock diseases caused high mortality amongst oxen cattle. and donkeys. Several farms also lost family workers
14 Towards More Sustainable Soil Fertility Management who chose to migrate from the area. This shortage of were often unable to do this because of labour draught power and human labour meant that the constraints. However, in most cases use of organic households in question were forced to put an fertiliser was close to what had been planned despite increased area under fallow and to engage in more high transport costs, incurred as high mortality rates monocropping than had been planned. Maize acreage amongst donkeys necessitated the hiring of tractors for was often increased at the expense of sorghum and transport.' While all farmers tried maize/dolichos millet, because of time constraints. Class III farms, intercropping, Class I and II farmers planted which were less well-endowed at the outset, were approximately double the area of Class III farmers. more vulnerable to these changes than the other However, many farmers did not harvest this fodder classes, and their degree of implementation was crop following a second wave of animal mortality in correspondingly poorer. the village. Thus far only 3 farmers have experimented with MAJOR ACHIEVEMENTS (SEE TABLE 8) contour farming. This was done in the framework of Farmers from Classes I and II constructed a new type a test executed in collaboration with ICRISAT (Mali). of fodder storage facility, using local materials and However, the considerable impact of this technique on wire fencing (provided on credit by the Association soil and water conservation attracted many other Villageoise) to protect stalks from straying animals. farmers, several of whom have decided to try contour Class III farmers were unable to construct such farming during the next cropping cycle. facilities due to time constraints and lack of creditworthiness. The amount of cereal stalks that FARMERS' OPINIONS OF THE PROCESS were stored for fodder during the dry season therefore Farmers were generally very positive about the utility varied considerably (from 1,500 kg to more than 8,000 of the resource flow models. These helped them to kg per household). Farmers also experimented with identify and to plan priorities, as well as to keep enriching the cereal stacks using a chaff-cutter and a records of changes they had made. According to the mixture of urea and molasses as well as salt blocks. test farmers, such planning and recording of activities Due to livestock mortality during the dry season and motivated them to implementation. Some of the early rains, however, it turned out that only small farmers share their resource flow models with other amounts of the stored fodder were actually needed. household members and use them as a basis for Surplus cereal stalks were used as cattle litter or were discussion. For this reason they felt that other transferred to the compost pit. • household members should be trained in mapping Given the severe decrease in livestock numbers, techniques. and hence manure availability, farmers began investing Another positive outcome has been that more and more in organic fertiliser production through more farmers are now taking part in the presentation composting(one of the farmers composted more than meetings at village level. Increasingly, farmers lead the 14 tonnes of cereal stalks). Some farmers used rock discussions and use this forum to exchange results phosphate to improve the quality of the organic and stimulate others to action. fertiliser. Although Class III farmers without carts had planned to instal compost pits near their fields, they 5 Assessing the impact on the sustainability of the farming systems Table 8. Planned activities that were implemented in 1995 5.1 Purpose Class I Class II Class III The effect of the action-research,on the adoption of improved soil fertility technologies can be evaluated Composting' • near house 100% 100% 60% through the yearly planning-evaluation cycle; the • near field 60% 50% 20% impact assessment is thus part of the participatory , .....•••• planning process. However, to assess the overall 'new' fodder storage' 100% 100% 20% ••• •••••••. .•••••••• •••• impact of the improved soil fertility management Fodder (average per practices on the sustainability of the farming system, class) appropriate parameters to describe what is meant by • stored (carts) 2 38 25 12 sustainability need to be identified. These parameters, • chopped (carts) 1.5 1 0.8 which represent a means of quantifying sustainability, Maize/dolichos 0.5 0.5 0.35 need to be easily measurable, objective, widely- (average per farm in ha) accepted, and based on time series data. The key aspect of this method is that data gathered in Contour ridges' 40% 0% 20% participatory ways and traditionally considered to be Percentage of the test farmers who realised their plans 'soft' can then be used to develop indicators for 'hard' 2 1 cart load = 120 kg of cereal stalks system sustainability; no further formal surveys are
15 Agricultural Research and Extension Network Paper 63
within the farm are recorded. Four types of data file Table 9. Users and uses of research results are included: residue outflows from plots; crop outflows from plots; mineral and organic fertiliser User group Purpose to which results have been put inflows; resources entering or leaving other areas of the farm (beyond cultivated plots). The quantity and Researchers • To evaluate the overall methodology used source of each inflow or outflow are detailed. For an • To evaluate the different tools and the example see Annex 1. Traditional measures used by effect they have on fertility farmers in their flow diagrams, such as cartloads, are management practices converted into standard units for the purposes of data the effect of the new • To evaluate analysis. Although these estimates are rough, they technologies on ecological, social and economic stability in southern Mali come straight from the farmers' experience which means that although the variance of the measurement Farmers • To facilitate comparison between their error might be high, its bias can be considered quite own and their neighbours' performance low. • To make comparisons between their The data files are then used to generate the own practices and extension sustainability parameters. The idea of these parameters recommendations is that they should quantify for example the levels of • To facilitate year-on-year comparison maintain a particular of their own fertility management key inputs that are required to . practices farming systems; they take the form of ratios (such as organic fertiliser use per hectare or per head of cattle). Extension • To draw comparisons between their guidelines services own recommendations and the Once developed they can then be used as current practices of farmers placed in for recommendations and standards by which farmers different categories or living in can monitor their own progress. The sustainability different areas parameters which were selected were based on the • To revise recommendations where necessary key criteria identified by the farmers during the research in Noyaradougou (they are in fact common Policy- • To evaluate the effects of their own in which research has been makers and policies or the programmes they are to all 4 villages donors supporting conducted) (see Table 3). These criteria fall into 3 groups: (1) use of crop residues, (2) production and use of organic fertiliser and (3) dosage of mineral fertiliser. The value of the ratios is that they combine required (Harrington, 1991; Young and Ryan, 1992). farmers' own criteria for good practice (classified into This section describes the way in which the these 3 types) with their own observations about research team has developed sustainability parameters, underlying socio-economic factors. Although farmers once again drawing on data from the village of do not themselves think in terms of ratios(parameters) Noyaradougou. However, this is not the only use to they are able to understand and use them for which research results have been put. Table 9 comparison between farms and over time. In this way, summarises the many users and uses of the results. researchers add value to farmers' own data. Although farmers' criteria are the leading guidelines 5.2 Data analysis and the development of in assessing sustainability of the production systems, sustainability parameters other parameters, such as the flows between village- Data generated during the preparation of the resource and farm-level and economic efficiency, will also be flow models was first transferred to monitoring forms taken into account in the future. Also, parameters Figure 7). and thence into a computer database (see which approach more qualitative aspects of the farm designed so that all details (even This database is and its members, such as training, knowledge and of soil types within fields) are captured along changes internal household organisation, have yet to be with farm-level and field-level characteristics, where determined. relevant, as well as inputs, outputs, sources and destinations. The data is organised in a pyramid structure with increasing levels of detail. On the first 5.3 Results level, data about each farm (such as labour Various sustainability parameters, calculated using the availability, number of cattle, cotton production and data from the resource flow models from fertiliser use) is recorded. At the second level of detail Noyaradougou are shown in Table 10 and Figures 8, characteristics of different fields within the farm and 9, 10 and 11. The parameters facilitate comparison: plots within the field are recorded. At the third level between the 3 farm classes; over time; and with resource flows entering or leaving each plot or area existing extension or research recommendations.
16 Towards More Sustainable Soil Fertility Management
Figure 7. Schematic representation of information flows within the action-research programme
Class 11 average Agricultural Research and Extension Network Paper 63
Figure 8. Crop residue recycling (kg/ha)
CROP RESIDUE RECYCLING Legend Litter Fodder 1200 Compost
1000
BO0 co s00
400
200
Class I Class Ill Class I Class III 1993/94 1994195
Figure 9. Crop residue recycling (kg/TLU)
CROP RESIDUE RECYCLING
400
350
300
450
Di00
150
100
50
0 Class I Class III Class I Class III 1993/94 1994/95
18 Towards More Sustainable Soil Fertility Management
Figure 10. Organic fertiliser utilisation (kg/ha)
ORGANIC FERTILISER PRODUCTJUTILISATION
700
600
500
2100
300
200
100
Class I Class Ill Class I Class III 1993/94 1994/95
Figure 11. Manure production per TLU
MANURE PRODUCTION ...100111111111ilop...
250
200
?,50
100 50 z Class I Class III Class I Class III 1993194 1994/95
19 Agricultural Research and Extension Network Paper 63
CROP RESIDUE RECYCLING Mineral fertiliser application on cotton is on average Figures 8 and 9 both show year-on-year improvement higher than the recommended doses, especially for in crop residue use for Class I and Class III farms. Class III farms.13 These farms grow less cotton, but Figure 8 shows that one year of action-research had a more intensively, although they did, on average, positive effect on the degree of residue recycling in slightly decrease the dose of cotton complex in the both classes. However, recycling was substantially second year of the research. This might reflect their higher among Class I farmers, who were 3 times less greater use of organic fertiliser. In the first year, likely than Class III farmers to burn their crop mineral fertiliser application on cereals was much residues, and who used more of their residues as litter lower than the extension recommendation. Class I for penned cattle. After one cycle of the action- farms, however, used more minerAl fertiliser on cereals research, burning of residues decreased considerably, than Class III farms. For all classes, the doses of urea especially among Class III farmers, and the overall and cereal complex increased considerably after one disparity in degree of recycling which had existed cycle of action-research. between Class I and Class III had more than halved. In the second year of action-research use of 5.4 Plansfor thefuture residues as litter decreased slightly, owing to high During evaluation sessions with the different classes of mortality among cattle, but this was compensated for farmers the usefulness of the different parameters will by an increase in composting. High mortality among be discussed in order to ensure that the most donkeys and the consequent constraints on transport appropriate parameters have been selected. It is forced farmers to leave more residues in the fields, possible that new parameters will be developed in the which made them vulnerable to termites. future as research with new groups of farmers yields Figure 9, however, shows that both classes of farms different criteria. If this is the case, additional data can fall well short of the 750 kg of litter/TLU which is be collected and monitored in existing research recommended to produce good quality manure in the villages. ESPGRN will also continue to monitor existing north Guinean zone (Bosma et al., 1993). parameters and will aim to use them to develop better targeted extension recommendations. PRODUCTION/USE OF ORGANIC FERTILISER The quantities of organic fertilisers transported to the 6 Perspectives and challenges fields (per hectare and per TLU) for 1993-94 and The approach described in this paper has been tested 1994-95 are presented in Figures 10 and 11. Both for some years in a research setting as well as with parameters show the same trend. Unlike crop residue extensionists. So far the results are satisfying; the recycling, Class I farmers do not produce substantially methodology is quick and provides effective tools for more organic fertiliser than Class III farmers. After a analysing and understanding the diversity of farming year, Class III farmers seemed even to be doing better households. It is participatory and action-oriented and than Class I farms in this area. Hence, Class III farms thus creates common ground for discussion and (which cultivate smaller areas) seem to be more exchange of views between farmers and sustainable in terms of maintenance of organic matter researchers/extensionists. content of the soil than the larger, Class I farms. The Farmers appreciate resource flow analysis as a tool quantities are, however, still considerably below the for improving soil fertility management. Visualising the recommended rate of 2.5 tonnes/ha/year, to ensure a minimum level of organic matter in the soil (van der Table 10. Quantities of mineral fertilisers applied Pol, 1992). (averages of farms by class of farm) Manure production per TLU shows the same tendency. Although in the first year, Class I farms Kg per Class I Class Ill Hectare produced more manure per TLU than,Class III farms, 1993— 1994— 1993— 1994- the increase after one cycle of action-research was 94 95 94 95 considerably higher for the Class III farms (Figure 11). COTTON' Again, though, the figures are well below the optimal • Urea 74 69 71 70 Guinean production of 1,000 kg/TLU for the north • Cotton zone (Bosma et al., 1993). Given the relatively high complex 150 159 183 165 doses of litter used in 1994-95, manure production in 1995-96 is expected to be closer to this recommended CEREALS' 54 74 18 45 target. • Urea • Cereal complex 50 82 18 56 DOSAGE OF MINERAL FERTILISER Table 10 presents the quantities of mineral fertiliser Number of 5 5 5 5 applied by class of farm. farms
20 Towards More Sustainable Soil Fertility Management
flows enables them to analyse their own strategies and imply changes in the way that they themselves are practices of management and the combination of monitored. The costs of such changes are likely to be analysis and exposure to information on new high, especially during the time-consuming training technologies motivates them to plan changes. Planning period. maps for the next season's objectives help them to One way to reduce costs would be to reduce the identify priorities and to keep track of earlier number of visits made to each village by the extension improvements. The regular feedback of individual workers involved in the process. It is therefore results to the village meetings facilitates comparison important that the extension services continue with the between farmers with similar resources and objectives. training of farmers, in the framework of the This stimulates other farmers to exchange experiences Association Villageoise, who can act as village and to take action themselves. Discussions may also intermediaries. Such intermediaries can take on tasks lead to village-level resolutions such as to limit the such as the preparation of resource flow models, clearing of new fields in fragile areas, to make more leaving the extension workers to organise workshops, rational use of the pastures, and to implement demonstrations and inter-village visits. Extension communal erosion control measures. workers will also need to ensure that all farm Some young volunteer farmers have regularly households have access to the services of the village accompanied the research team as it has worked with intermediaries. One question which must be resolved test farmers to develop resource flow models. These with the village is how to remunerate these farmers people are now capable of conducting the exercise for their services. Experiences from other countries alone and are prepared to assist new farmers who could help enrich the debate on the issue of payment would like to prepare resource flow models of farmer-extensionists, although the issue of themselves. compensating core members of the Association The methodology has been developed to serve both Villageoise, involved in credit and marketing in researchers and extensionists. However, for a further relation to cotton, is not new in southern Mali (Lopez, fine-tuning a distinction has to be made between these 1996). 2 groups of users. 6.2 Research 6.1 Extension The resource flow models drawn by farmers have Earlier global village diagnoses had shown that soil proved to be a powerful and accurate tool for fertility management was a priority for farmers. The information collection. They are comparable to a CMDT extension services therefore supported this classical semi-directed questionnaire but the pictorial action-research from the outset. depiction of flows allows for more reliable and Individual extension agents especially appreciated complete data collection, since omissions and mistakes the resource flow models which clearly interested are immediately visible. Another major benefit is that farmers and provided a valuable focus for group farmers not only provide information but also discussion. However, they found the analytical phase participate in the analysis itself. The map enables them to be rather time-consuming, complex and demanding to keep track of the interview and to identify their in terms of their own skills. This phase also requires own constraints. multi -disciplinary input, because of the complex Researchers will also be working to ensure that the nature of soil fertility management, and so is difficult interview guides are well structured so as to ensure for extension agents to work alone. systematic collection of all essential data. This is Discussions are now underway on how to simplify important since the results will be compared between the process of identification of key criteria and farmers and over time and many different individuals classification of households, as well as to develop a will be involved. One bias in the present methodology clearer procedure for the selection of 'test' farmers. may be the reliance on group interviews and resource The idea is to involve the Association Villageoise. persons whose background is not accurately known. Interview guides are also to be simplified and ESPGRN Thus far group interviews seem to have worked well is currently working with the CMDT extension service and informants seem to have been aware of the to this end. management strategies of their peers. Individual However, the extension service must recognise the interviews with a representative of each household overall implications of using this new model. The may, however, have to be added in future. change from a top-down, supply-driven mode of Researchers must continue to focus on evaluating operation will put more demands on the skills of the effects of the approach, how it seems to be extension workers, especially in facilitation, analysis, influencing the adoption of improved technologies, linking problems with solutions and identifying and what effect it is having on local production technologies. Extension officers will also have to form systems and their sustainability. There is also a need partnerships with farmers. All these new demands to further upgrade methods such as the ones
21 Agricultural Research and Extension Network Paper 63
described here, which allow for quantification and is to get an idea of where leakage or mining in the statistical analysis without sacrificing farmer farming system occurs and where accumulation takes participation. One reason for this is to keep place. When this is linked to the farm classification, it researchers interested in using such tools and will be possible to evaluate nutrient balances in methodologies. Since researchers are often evaluated relation to management practices and socio-economic on the basis of quantified, scientific results, there is a farm characteristics, thereby adding significant value to risk that they will soon return to more 'classical' the analysis. The nutrient balance exercise may also research methods if efforts are not made to refine PRA result in further targeting of improvements to the methodologies. different classes of farm. Whether or not this type of Further work is also needed to test the usefulness information is useful in communications with farmers of the sustainability parameters in assisting farmers to still needs to be assessed. plan their activities. Feedback from farmers will Finally, attention must be paid to developing therefore be essential. The idea is to 'add value' to parameters which reflect inter- and intra-household //farmers' criteria and to 'use' these parameters to influences on decision-making processes. The improve farmers' planning and evaluation of collection of data on decision-making processes management improvements. regarding soil fertility management will also assist To obtain a better idea about the performance of policy-makers in tracing through the effects of various the farm as a whole and of the linkages between the changes in economic incentives, socio-economic different sub-systems within it, a relational flow conditions or the general macro-economic analysis has to be made at the farm level. Since environment, thereby adding further value to the different types of products leave or enter the farm and methodology. Overall, we hope that the methodology flow between the different farm enterprises, a presented will strengthen the collaboration between common unit of measurement is needed to make a farmers, researchers, extensionist and policy-makers, balance; nutrient flow analysis offers this possibility. which is needed to arrive at more sustainable soil The aim of making a nutrient balance at the farm level fertility management.
22 Towards More Sustainable Soil Fertility Management
ANNEX 1 Organisation of the data files
Data file A: Farm characteristics 0
Organic Cotton Organic Organic Organic Village Farm Cotton fertiliser Labour Cattle production fertiliser on fertiliser on fertiliser number number area (ha) per ha of (kg) cotton cereals per labour cotton 1 1 8 4 2200 2 1500 20 750 188 1 2 6 3 1400 1 200 0 200 33
Data file B: Field and plot characteristics
Village Farm No_field No_plot Area Crop number number
1 1 1 1 1— cotton-
1 1 1 2 1.3 corn
1 1 2 1 1— cotton,.
1 1 2 2 0.7 millet
Data file C: Fertiliser inflows by plot
Village Farm No_field No_plot Type of input Quantity Origin number _ number
1 1 1 1 Organic fertiliser 1500 Pen
1 1 . 1 1 Mineral fertiliser 150 CMDT
1 1 1 2 Organic fertiliser .20 Pen
1 1 _ 1 2 Mineral fertiliser 0 CMDT
The use of organic fertiliser, for example, is an fertiliser is represented by one line, and an application important parameter in analysing soil fertility. It is, of 150 kg of mineral fertiliser on the same plot however, not the absolute quantities that are represents another one (file C). To make this interesting, but the relative quantities: organic fertiliser information useful, it needs to be combined with plot used per hectare, or per head of cattle, or per labour information on the crop grown on that plot, and unit. These numbers make comparisons over classes aggregated by farm and by crop or group of crops, of farmers possible, or the monitoring of changes in a resulting in the amount of manure used by farmer. farm over time. These results are then merged into the basic farm level To calculate these numbers, several steps are data file A (arrow 2). necessary. Labour and cattle are already in the basic Finally, the ratios can be calculated in the farm level database (file A), organised per farm. Areas, on the file. In the example, organic fertiliser on cotton is other hand, are organised by plot (file B). It is divided by area under cotton to obtain kg/ha for therefore necessary to first aggregate plot areas by cotton (arrow 3). The organic fertiliser applications on farm for each crop, and then merge the aggregated file the different crops are added and divided by the UTL, of area (arrow 1) onto the base file. to obtain an indicator of how much of the potential The input flows are organised with one line per manure production is actually used. flow (file C). An application of 1,200 kg of organic
23 Agricultural Research and Extension Network Paper 63
Endnotes 8. Class II has only 2 farms in the sample, which 1. Credit for seed, fertiliser and pesticides is makes the data for this class quite unreliable. For supplied according to the area which the farmer this reason only Class I and Class III are plans to dedicate to cotton during the next represented here. More farms have been added season. Credit and inputs are supplied through to the sample since 1995. the village association (AV; see Box 3). It should 9. A Tropical Livestock Unit (TLU) represents an be noted that the CMDT is transferring credit animal with a need for energy ,equal to 1,300 delivery to the banking sector and is currently fodder units and corresponds to a cow of 250 kg. considering withdrawal from mineral fertiliser Under sub-Saharan conditions, an adult cow is supply. It has already begun to withdraw from equal to 0.9 TLU, an oxen 1.5 TLU, a calf 0.25 insecticide and herbicide provision(De Groote et TLU and a small ruminant 0.2 TLU (Breman and al., 1996). de Ridder, 1991). 2. Cereals grown in rotation with cotton gain some 10. Malian Rock Phosphate is called PNT (Phosphate indirect benefit from the fertilisers used on the Naturel de Tilemsi). It contains about 28% P205 cotton. and 40% CaO (Samake, 1987). 3. In all cases guides are used. These allow 11. One alternative would be for Class III farmers to researchers/extensionists systematically to increase their holdings of cattle (and hence explore the selected topics, using questions manure production) and carts (hence ease of based on working hypotheses. It is important to composting residues). There are 2 difficulties maintain flexibility but experience has shown with this. The first concerns the cost of this that better results are obtained with interview option, the second the requirements for guides. These also allow for better comparison management of livestock if these are to between cases and over time. Nevertheless, contribute to, rather than worsen, soil fertility understanding reasons for farmers' behaviour management. through probing remains the major challenge Cattle are generally seen as one of the causes (Diarra et al., 1995). of increasing degradation. At the same time, 4. The term catena describes 'a sequence of soils of however, they are a necessary part of an about the same age, derived from similar parent integrated crop-livestock system. The problem material and occurring under similar climatic lies in the farmers' management of their cattle. conditions, but having different characteristics For example, if a farmer has too many cattle to due to variation in relief and in drainage.'(Brady, manage easily, he tends to leave them to graze 1984). full-time on the common pasturelands. This 5. Initially only 24 households were identified. This means that he is not able to collect their manure reflects the dynamic situation in the village with to use as organic fertiliser, as he would if the regard to the splitting-up of families (see Section cattle were penned for some of the time, for 2). example at night. Thus, overstocking contributes 6. A territory unit is a demarcation of the village to soil degradation. Paradoxically, however, to territory as made and known by all farmers; each produce sufficient manure to maintain an unit has a distinct name, which often relates to adequate organic matter level in the soil, it would something typical or to a special feature. be necessary to increase the total number of Sometimes the name indicates a big stone or hill, cattle in southern Mali. Bosma, Bengaly and a fertile zone, or a zone of wood, cutting. A Defoer (1993) have calculated that there is a territory unit is also sometimes called after the need for 30 to 35 TLU/km2 in order to produce first farmer who cultivated it. The limits of the the required amount of manure (2.5 territory units are often natural boundaries, such tonnes/ha/yr) to maintain minimum soil organic as rivers, or roads, although this is not always the matter levels. For this to succeed these TLUs case. The units do normally not follow soil types. have to be managed correctly, with crop residue A unit is also not really linked to a family recycling, fodder production and litter use. One property, although it is common to find TLU, if kept penned and provided with about households of the same family in the same unit. 750 kg of litter, can produce about 1 tonne of 7. The amount of land dedicated to cotton is manure per annum. The most critical period is at determined by a number of features. These the end of the dry season when, for about 3 include: degree of food self-sufficiency and grain months, the animals should be kept penned for reserves at the start of the season; amount of almost 24 hours a day, and fed with recycled family labour; indebtedness and need to pay residues, fodder and cotton cake. back credit; and courage. Soil types and access to 12. The cost of transportation was 2,500 FCFA for a money are relatively unimportant. 320 kg trolley load (= 7.8 FCFA/kg organic
24 Towards More Sustainable Soil Fertility Management
fertiliser), for a home to field distance of 3-4 km. methodologiques. Article presente au symposium du This is a very high cost given that the value of RESPAO, 20-2 Juin, 1994 a Cotonou, Benin. organic fertiliser, calculated on the basis of yield Defoer, T. and Hilhorst, T.(1995) In search offarmer increase when applied on cotton (DRSPR, 1992) participatory approachesfor research and extension or on the basis of mineral content, is on average in southern Mali. Paper presented at the ETC 7 FCFA/kg (La vigne Delville, 1995). International Work Week, 30 October - 4 13. Extension recommendations per hectare are: for November, 1995, Kericho town, Western Kenya. cotton, 50 kg of urea (46N) and 150 kg of cotton Defoer, T., Hilhorst, T., Kante, S. and Diarra, S.(1995) complex(12N -22P205-14K20-5S-2B); for maize(the 'Analysing the diversity of farmers' strategies.' ILEIA most important cereal in terms of mineral Newsletter Vol. 11 (No. 2). fertilisation) 100 kg of urea (46N) and 50 kg of De Groote, H., Kebe, D. and Hilhorst, T.(1996) Rural cereal complex (15N-1513205-15K20) (CMDT, Financial Services in southern Mali: Can the Supply 1988). cover the Need? Paper prepared for the AAEA Annual Meeting, 28-31 July, San Antonio, Texas, References USA. Berckmoes, W., Jager, EJ. and Kone, Y. (1990) Dent, B. (1995) 'Theory and practice in FSRE: 'I:intensification agricole au Mali-sud. Souhait ou Considering the role of modelling.' In: Journalfor realite?' KIT Bulletin No. 318. Amsterdam, Farming Systems Research-Extension, Vol.5, No.1, Netherlands. pp.31-44. Bosma, R., Bengaly, M. and Defoer, T.(1993) Pour un DRSPR.(1992) Comtite Technique Regional: Resultats systeme durable deproduction: augmenter le betail. de recherche de la compagne 1991-92 du Equipe Systemes de Production et Gestion de DRSPR/Sikasso. Department de Recherche sur les Ressources Naturelles (ESPGRN): Sikasso, Mali. Systemes de Production Rural, Equipe de Sikasso: Brady, N.C.(1984) The Nature and Properties ofSoils. Mali. 9th Edn. Collier Macmillan: New York. Diarra, S., Defoer, T. and Hilhorst, T.(1995) 'Pour une Breman, H. and de Ridder, N. (1991) Manuel sur les cartographie paysanne du terroir villageois.' Note paturages des pays Saheliens. CABO-DLO: methodologique. Equipe Systemes de Production et Wageningen, Pays-Bas. Gestion de Ressources Naturelles (ESPGRN): Brons, J., Diarra, S., Dembele, I., Bagayoko, S. and Sikasso, Mali. Djouara, H. (1994) Diversite de gestion de ESPGRN. (1994) `Gestion paysanne de la fertilite. l'exploitation agricole. Etude sur les facteurs Resultats d'un diagnostic Rapide. Rapport d'etape.' d'intensification agricole au Mali-sud.' Document Document No. 94/23. Equipe Systemes de No. 94/33. IER/ESPGRN: Sikasso, Mali. Production et Gestion de Ressources Naturelles Brossier, J. and Chia, E.(1994) 'Participatory research: (ESPGRN): Sikasso, Mali. Water quality and changes in farming systems.' In: ESPGRN. (1995) 'Comment on Agricultural Research Dent, J. and Gregor, M. (eds). (1994) Farm and and Extension Network Paper 54: On Building a Rural Systems Analysis: European perspectives. Partnership between Farmers and Researchers in CABI: Wallingford, UK Mali', by M-H. Collion. ODINewsletter 32,July 1995. Campbell, A.(1994) Landcare in Australia: Spawning Overseas Development Institute: London. New Models of Inquiry and Learning for Hamilton, N.A. (1995) Learning to Learn with Sustainability. Paper presented at the International Farmers: A case study of an adult learning Symposium on Systems-Oriented Research in extension project conducted in Queensland, Agriculture and Rural Development, 21 to 25 Australia (1990-95). PhD. Thesis Agricultural November, 1994, Montpellier, France. University of Wageningen: Netherlands. CMDT. (1988) Seminaire sur l'avenir de la filere Harrington, L.W. (1991) Measuring sustainability: coton au Mali. CMDT: Bamako, Mali. issues and alternatives. Paper presented at the 11th CMDT.(1995) Le diagnostic global participatif, Fiche Annual Farming systems Research and Extension Methodologique. CMDT: Bamako, Mali. Symposium, 5-10 October 1991, East Lansing, Chambers, R. (1993) 'Methods for Analysing by Michigan. Farmers: the Professional Challenge.' Journal for Hoefsloot, B., Van der Pol, F. and Roeleveld, L.(1993) Farming Systems Research and Extension, Vol.4(1). `Jacheres ameliorees. Options pour le Collion, M-H. (1995) 'On Building a Partnership in developpement des systemes de production en Mali between Farmers and researchers.' Agricultural Afrique de l'Ouest.' KIT Bulletin No.333. Research and Extension Network Paper No.54. Amsterdam, The Netherlands. Overseas Development Institute: London. Huijsman, A. (1995) 'Towards the Concerted Defoer, T. and Diarra, S.(1994) Diagnostic participatif Management of Agro-Ecosystems.' Journal for de la gestion de fertilite des sols: aspects Farming Systems Research and Extension.Vol.5(1).
25 Agricultural Research and Extension Network Paper 63
IER. (1994) Manuel d'organisation de l'Institut Ming, N. (1994) Creating Human Platforms to d'Economie Rurale. IER: Bamako, Mali. Manage Natural Resources: First Results of a Kante, S. and Defoer, T.(1994) 'How farmers classify Research Programme. Paper presented at the and manage their land: Implications for research International Symposium on Systems-Oriented and development activities.' IIED, Dryland Research in Agriculture and Rural Development, 21 Networks Programme: Issue Paper No. 51. to 25 November, 1994, Montpellier, France. International Institute for Environment and Samake, F. (1987) Contribution a la valorisation du Development: London, England. Phosphate Naturel de Tilemse (PNI) par l'action La vigne Delville, Ph.(1995) 'Le point sur ... La fertilite d'acides mineraux et de composes organiques des terres en Afrique soudano-sahelienne.' Draft. humifies. Thesis presented at The l'Institut GRET: Paris, France. Polytechnique de Lorraine, France. Leloup, S. and Traore, M. (1989) La situation Scoones, I. and Thompson, J. (1994) Beyond Farmer fourragere dans le Sud-Est du Mali: une etude First: Rural People's Knowledge, Agricultural agro-ecologique. Equipe Systemes de Production et Research and Extension Practice. Intermediate Gestion de Ressources Naturelles (ESPGRN): Technology Publications Ltd., London, England. Sikasso, Mali. Thrupp, L.A., Cabarle, B. and Zazueta, A. (1994) Lightfoot, C., Dalsgaard, J.P., Bimbao, A.M. and Participatory Methods in Planning and Political Fermin, F. (1992) Farmer Participatory Procedures Processes: Linking the Grassroots and Policy for for Managing and Monitoring Sustainable Farming Sustainable Development. Agriculture and Human Systems. ICLARM Contribution No. 892. Values, Summer-Spring, 1994. International Center for Living Aquatic Resources Van der Pol, E (1992) 'Soil mining: an unseen Management, Manila, Philippines. contribution to farm income in southern Mali.' KIT Lightfoot, C., Noble, R. and Morales, R., 1991. Training Bulletin No. 325. KIT, Amsterdam, Netherlands. resource book on a participatory method for Van der Pol, F. and Giraudy, F. (1993) Etude sur les modeling bioresource flows. International Center for relations entre pratiques d'amelioration des sols et Living Aquatic Resource Management (ICLARM), variables socio-economiques dans la zone Mali- Educational Series 14, 3Opp. Sud. IER/KIT/CMDT, Bamako, Mali. Lopez V. G. (1996) 'The village extensionist in Vierstra, G. (1994) La perception des paysans de la developing nations.' In: Scarborough, V. (ed): degradation des sols et des politiques pour la 'Farmer-led approaches to extension: Papers combattre. Club du Sahel, OCDE, KIT/IER/CMDT, presented at a workshop in Philippines, July 1995.' Amsterdam/Bamako, Mali. Agricultural Research and Extension Network Paper Vries, J. de and Prost, L. (1994) Le parc ameliore. No. 59a. Overseas Development Institute: London. Etude de son adoption par les paysans dans la Pieri, C. (1989) Fertilite des terres de savanne. Bilan zone Mali-sud. CMDT/DDRS, Koutiala, Mali. de trente ans de recherche et de developpement William, R., Lev, L., Conway, F., Deboodt, T., agricole au sud du Sahara. Ministere de la Hathaway, R., Todd, R. and Smith, F. (1994) cooperation, CIRAD/IRAT: Paris, France. Improving Oregon's Natural Resources: PIRL.(1989) 'Projet inventaire des ressources ligneuses Collaborative Learning, Systems Approaches, and et occupation agricole des terres au Mali.' Notice de Participatory Action Research. Paper of the Cercle. Cercle de Koutiala et de Kadiolo, SCET International Symposium on Systems-Oriented AGRI CTFT. Research in Agriculture and Rural Development, 21 Richards, P. (1994) 'Local knowledge formation and to 25 November, 1994, Montpellier, France. validation: the case of rice production'in Central Young, M.D. and Ryan, S.A. (1992) Using Environ- Sierra Leone.' In: Scoones, I. and Thompson, J. mental Indicators to Promote Environmentally, (eds). (1994) Beyond Farmer First: Rural People's Ecologically and Socially Sustainable Resource Use: Knowledge, Agricultural Research and extension A Policy-Oriented Methodology. EPAT/MUCIA practice. Intermediate Technology Publications Ltd: Research & Training: Environmental & Natural London, UK. Resources Policy & Training Project, Madison, USA.
26 Acknowledgements The authors are indebted to all members of the ESPGRN team for their contribution to the (ongoing) development of the action-research approach on soil fertility management. We would like to thank M'pie Bengaly, Souleymane Diarra, Siaka Bagayoko, Diakaridia Diabate, Moumine Traore, Robert Berth& Amadi Coulibaly, Mari-Cecile Sidibe, Hamady Djoura, Abdoitlaye .Kamara, as well as the farmers of Soussoula, Noyaradougou and Gongasso who endured ESPGRN's testing. Regular KIT consultancies from W Stoop strongly contributed to the development of the approach and from P Penninkhoff assisted in the inclusion of gender-related aspects in the different tools used. Representatives of CMDT, the cotton research programme and ICRISAT/CIRAD (Mali) (Kalifa Traore and Jacques Gigou), contributed to different phases of the action-research. Useful comments on earlier drafts were made by Rita Joldersma and Arnoud Budelman. We are indebted to Marijke Loosvelt for her careful work on editing the boxes, to Oumar Fatogoma Traore for the maps of Mali and diagrams, to Abdoul Karim Diarra for carefully copying farmers' maps and Siaka Traore for entering the data. A REN
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