Monitoring of livestock health and production in sub-Saharan Africa

Preventive VeterinaryMedicine25 ( 1995) 195-212

Monitoring of livestock health and production in sub-Saharan Africa P.N. de Leeuwav*, J.J. McDermottb,C,S.H.B. Lebbie” “International Livestock Research Institute, P.O. Box 30709, Nairobi, Kenya “Department of Public Health, University of Nairobi, P.O. Box 29053, Nairobi, Kenya ‘Department ofPopulationMedicine, University of Guelph, Guelph, Ont. NlG 2W1, Canada

Accepted10 August 1995

Abstract

We begin by stressing that relevant and adequate information is an essential ingredient of efficient decision-making processes aimed at optimising the performance of livestock enterprises. Such decisions are universally made, so that though different approaches may be required, animal health and production monitoring (HPM) is as important in sub-Saharan Africa (SSA) as it is in livestock systems in other parts of the world. To set the scene for our discussion of HPM in SSA, we broadly describe the main African production systems in tabular form, categorised by ecological conditions, production goals and input and output relations within a broad farming systems context. Subsequently, the scope and diversity of HPM in SSA is reviewed. This review reveals that in 2 decades of system monitoring, a wide variety of objectives have been tackled from broad system description and constraint diagnosis to more focused research to identify and quantify the impact of disease and other specific factors on the productivity of cattle and small ruminants. There have been many monitoring clients, ranging from national governments through aid agencies and the scientific community, to individual farmers. To serve these diverse clients and their objectives, a plethora of methods and data collection techniques have evolved, which are briefly reviewed. Methods are often system-specific. As examples, we discuss the specific monitoring needs of two contrasting production systems (pastoralists in the arid and semi-arid zones and smallholder dairy farmers in the highlands of East Africa) to indicate how monitoring has contributed to our understanding of these systems and how monitoring might be better targeted to satisfy future needs. The impact of HPM on the “state of the knowledge’ of traditional African production systems are then summarised at two levels. The first includes specific health and productivity information gained while the second considers the more general lessons learned with respect to livestock enterprise functions and their impact on human welfare. Finally, future monitoring needs are discussed relative to changes in African livestock systems. It is anticipated that further specialisation and intensification

*Correspondingauthor. 0167-5877/95/$09.50 0 1995Elsevier Science B.V. All rights reserved SSDIOl67-S877(95)00547-1

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of livestock enterprises will require decision-support systems, many of which already exist in the developed world and could be adapted to SSA. Kqvwords:

Livestock; Health production; Africa; Monitoring methods

1. Introduction Managers of livestock organisations and enterprises from farm through to international level need to make sound decisions about utilising resources effectively. Such decisions seek to increase utility, by trade-offs between increasing production or profit and increasing survival and sustainability. Information is an essential ingredient for effective decision making and lack of information is a significant constraint. Thus, more attention needs to be paid to the efficient collection, management and analysis of livestock health and production information. An effective health and production monitoring (HPM) system must provide accessible, timely and valid information which satisfies the needs of the suppliers, managers and clients of the system (Morris, 1991). The scope of HPM has broadened over time. Earlier systems, such as the monitoring of production traits in genetic selection programmes for livestock, were targeted at individual animals. Subsequently, since the 196Os, herd-level health and production monitoring systems have evolved from routine animal health and reproductive monitoring to include a wider range of production indices and their genetic, nutritional and economic determinants (Radostits et al., 1994). In the late 1970s and early 1980s this herd focus expanded to a production system perspective (e.g. Shaner et al., 1982). For important production systems in sub-Saharan Africa (SSA), many valuable studies were published (see references in Table 3). Detailed and comprehensive information has been collected that provided valuable baseline information on health and productivity levels and some factors influencing these levels. Within the gradual evolution of monitoring and information systems there are still disagreements over the focus and strategies to be employed. There are two of particular interest to HPM in SSA. The first, debated at a recent symposium on smallholder livestock production in developing countries (Daniels et al., 1993)) is the relative merits of farmer-participatory (Chambers, 1993) versus more technical approaches (Morris and Leidl, 1993) to the collection of livestock health and production data. The second area of difference is on the type and intensity of monitoring. One obvious contrast is in the field of disease reporting. Many African countries attempt to estimate reportable disease occurrence from routine reports of veterinary departments rather than from periodic studies of sampled populations (e.g. Kitala et al., 1994). For health and production data, periodic surveys of sampled farms have been advocated and demonstrated as effective by Leech ( 197 la,b). In this paper, we plan to discuss health and production monitoring of livestock with special reference to SSA. We start by elaborating the general and specific reasons for livestock HPM in SSA. We go on to briefly characterise the major livestock production systems in SSA. We describe the scope and development of techniques and approaches used in monitoring livestock performance in traditional African farming systems and discuss specific monitoring needs for two contrasting production systems (pastoralists and small-

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holder dairy farmers) as examples of what has been learned and what approaches might work. Finally, we discuss the impact of monitoring on livestock production and what might be the monitoring needs in the future.

2. Purposes for livestock health and production monitoring The overall purpose of monitoring livestock enterprises is to identify constraints against and opportunities for improving livestock health and productivity. Relevant indicators of improved livestock output in SSA include increases in productivity levels, such as lactation yields for dairy cows or growth rates for calves, as well as less routinely collected variables such as changes in the distribution of income or the enhanced sustainability of the livestock enterprise (a range of variables are listed in Table 2). Defining constraints of necessity implies making judgements about whether health and productivity levels are lower than desired and in assessing factors associated with reduced levels. This could include defining these levels by either theoretical targets (Radostits et al., 1994) or in relation to measured levels of similar farms (McDermott et al., 1991). Some measures would be subjective and potentially changing such as acceptable rates of calf morbidity and mortality in low-input traditional systems; others would be more objective, such as the exclusion of foot and mouth and other trade-limiting diseases from livestock exporting countries like Zimbabwe and Botswana. Of particular interest should be an assessment of variations in health and production levels to help identify opportunities for improvement (Holden et al., 1993; McDermott et al., 1993). Dohoo ( 1993) described four practical applications of livestock health and production monitoring. In traditional African livestock systems, his first two categories (collection of baseline data and descriptive and analytic research) have been the most commonly applied. A third application, disease monitoring to support government regulatory functions such as movement controls and mass vaccination, while recognised as important, has been less successfully applied except in some southern African countries. The fourth and most actionoriented area of application, monitoring to improve the provision of services to farmers and their advisors, remains, as in other areas of the world, largely undone. More specific examples will be detailed later. As argued by Morris ( 199 1)) the design of monitoring systems should be determined by the needs of decision-makers. In SSA, decisions are taken at a number of client levels: farmers, local community groups (e.g. pastoralists, farmer cooperatives), government departments, national agricultural research and extension services (NARES), international research organisations and bi- and multilateral development agencies. Some information is uniformly needed at all levels but in many cases the scale of interest will vary. Farmers need information on the main health and productivity constraints in their farm or herd, their options for improving these, and on whether their management practices are sustainable over the longer term. The NARES require health and production indices for the major livestock systems in their country to guide extension, marketing and research planning, while international organisations have an interest in monitoring disease, production and environmental trends across countries, regions and continents.

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Table 1 Characteristics of the four major traditional livestock production systems in tropical Africa

Zone

Pastorahsts

Agro-pastoral&s

Croplivestock farmers

Crop farmers with livestock

A-SA

SA-SH

SA-SH-HL

SH-H-HL

1@40 lo-20 2-5

20-100 20-60 l-5

10 20 20 10 20

40 30 30 40

Densities People km-’ TLU km-* TLU caput Ownership ( % of total ) Camels Cattle Sheep Goats TLU

4-8 5-15 3-1.5

90 30 40 40 30

15-100 IO-60 l-2

10 10 20 10

Mobility

xxx

xx

X

Livestock (% of income)

> 90%

50-90%

lo-50%

< 10%

xxx xxx xx

xxx xx

xx

xxx

X

Major functions Cash income” Milkb Meat Traction Manure, dung

X

?

X

xxx

x

xx

X

“May include income from barter. ‘Both cash and subsistence income. Zones: A, arid; SA, semi-arid; SH, subhumid; H, humid; HL, highlands. Importance score: xxx, high; xx, medium; x, low. TLU, tropical livestock units.

3. Major livestock production systems in SSA Ruminant livestock play an important role in rural SSA, providing sustenance, cash income, insurance against risks in difficult environments, transportation, animal traction and manure. There are about 162 million cattle, 147 million goats, 127 million sheep and 13 million camels in SSA (Winrock, 1992). The contribution of ruminants to gross agricultural output ranges from 4% in countries in the humid zone to over 80% for arid and semi-arid zones (Winrock, 1992). Ruminant livestock in SSA are integrated into a variety of production systems each with different constraints, management practices, production goals and farmer priorities. The characteristics of the main production systems in SSA are summarised in Table 1. It can be seen that the importance of livestock wealth as a source of income and subsistence decreases inversely with increasing rainfall. Likewise, the functions of livestock (cattle in particular) broaden to include the delivery of traction, transport and manure.

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Table 2 Range of variables that have been collected at various levels of interest in traditional farming systems in tropical Africa Category

Variables collected

Natural resource utilisation

Resources Land use Land pressure Infrastructure

Climatic and edaphic conditions; vegetation, forage and browse as feed, water, fuelwood Arable land, fractions of cultivated land, natural pastures; cropping patterns; land tenure Human population and livestock densities (at farm, community, regional level) Administration, roads, communications, markets, schools, veterinary services

Production sysrern

Endowments Enterprise mix Socioeconomic characteristics

Land, labour, livestock, investments, (water, housing, equipment) ; equity and endowment variability Crops and cropping patterns, livestock, off-farm activities. Labour use and allocation, income and expenditure profiles, inputs and outputs by enterprise and whole farm

Livestock subsystem

Resources Productivity offtake Management Economics Constrainnts

Numbers/HH, species composition; wealth profiles; enterprises and production goals Reproduction, growth, mortality, milk yields, milk sales traction power, live animals for slaughter and sales, hides and skins (by species) Housing, mobility, herding, milking, health care, labour use and allocation Production costs, income profiles, benelit4ost analysis Disease risks, frequency of droughts and dry years, market efficiency, terms of trade

In terms of livestock wealth, presently about 70% of the livestock mass in SSA is in the hands of rural people who own and manage multipurpose enterprises in which livestock are an integral part. Among these, highly interactive systems are the most important, accounting for 40% of all cattle and one third of small ruminants. Another 20% are kept by agropastoralists who, due to the increasing population pressure, will become more sedentary. Countering episodic shortages of feed and water and attenuating cyclic ‘booms and busts’ in their livestock output are their major concerns. They, together with the pastoral producers, live in highly variable and unpredictable environments and account for half of the continent’s livestock mass (Table 1) . A minor share of the livestock wealth is kept by resource-poor farmers who have only small livestock holdings relative to their wealthier neighbours. While they contribute little to the aggregated output accruing from livestock, numerically, they may account for half the rural population (approximately 100 million people) and the few goats or sheep they own are very important to their welfare. 4. Scope of monitoring

interests

Research and monitoring of African rural production systems has been characterised by an enormous diversity of objectives ranging from the general to the specific. This is reflected

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in the wide range of monitored variables listed in Table 2. While these variables are of interest to many monitoring clients (e.g. farmers, extensionists, researchers and policy makers), naturally the interests of those directly conducting and funding monitoring have been dominant. These include development agencies, international and developed country research institutes, bilateral and multilateral donors and NARES. As detailed available information is scarce, descriptive approaches have been common: initially, many of these focused on natural resource assessment of regions within countries. Mapping and describing land quality (soils, landforms, vegetation) and land use were major activities in the 1960s and 1970s usually funded and/or executed by scientists of western countries in their ex-colonies (see Table 2 and review by Bunting, 1987). These data bases have provided backgrounds for recommendation domain characterisation in subsequent farming system studies and for the agro-ecological human support capacity framework developed by FAO (Higgins et al., 1987) _Aerial surveys were often used as an important tool in this process, particularly to assess the distribution and size of target livestock and wildlife populations in relation to grazing and water resources (e.g. Resource Inventory Management Ltd (RIM) (1992), de Leeuw and Milligan (1984) and Bourn and Wint (1994) in West Africa; Peden (1984) and de Leeuw (1990) in Kenya). Such broad characterisations have been augmented with more detailed field work. A notable example of this was the conduct of farm surveys as part of a large project to characterise agriculture systems in Kenya during the late 1970s (Jaetzold and Schmidt, 1983). Over 50 clusters of 30 farms each were sampled covering all districts in the agroecological zones of medium and high potential agricultural land. Many agricultural variables (e.g. farm size, land use and livestock holdings) were collected while in-depth household economic studies were conducted in selected areas (reviewed by Tiffen et al., 1994). Monitoring of livestock systems was most often linked to and funded by regional development projects. For instance, USAID funded a rangeland project in the pastoral zone of Niger which supported studies of the Wodaabe and Twareg pastoral production systems (Swift, 1984; Sollod 1991) . Likewise, the World Bank initiated an integrated development project in the fifth region of Mali, which includes the Inland Delta of the River Niger. This long-term project included in-depth socio-economic studies of production systems by International Livestock Centre for Africa (ILCA) (Swift et al., 1982; Wilson et al., 1983; Hesse et al., 1984). Similarly, UNESCO in northern Kenya financed IPAL (Integrated Project of Arid Lands), in which constraint analysis of pastoral systems, including disease impact on productivity, was an important component (IPAL, 1984). Within these broader systems, more detailed livestock studies have been conducted. Most commonly, the objective was constraint diagnosis and often a project’s time-scale determined whether this diagnosis was rapid or longer term. Rapid appraisals of livestock productivity have been conducted by one-off recording of breeding female progeny histories (coined interviewing cows (Swift, 198 1) ) to establish reproductive, mortality and offtake rates in sample herds (Wilson et al., 1984; RIM, 1992). Where time and resources have allowed, rapid appraisals have been augmented by longer term and in-depth studies of repeated visits. Longer term biological productivity monitoring has been conducted in a number of pastoral and agro-pastoral environments. In some of these studies (e.g. Borana in southern Ethiopia; Maasai in south-east Kenya; Fulbe in subhumid Nigeria; references listed in Table 3)) important socio-economic variables on labour, income, expenditure and

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Table 3 Examples of productivity

monitoring

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studies for cattle in sub-Saharan

Africa

Zone

Country

Breed

Reference

Pastoralists A A-SA SA-SH

Niger Kenya Ethiopia

Zebu Zebu Zebu

Wilson et al. ( 1984) Bekure et al. ( 1991) (C) Coppock, 1994 (C)

Agropasstoralists SA SH SH SH

Mali Nigeria Benin C&e d’Ivoire

Zebu Zebu Z.xBos.t. Bos.t.

Wagenaar et al. ( 1986) von Kaufmann and Blench (1986); Dehoux and Hounson-Veh (1993) Itty (1992) (E)

farmers Mali Mali Gambia Gambia Ethiopia Ethiopia Ethiopia

Zebu Zebu Boss. Bos.t. Zebu Zebu Zebu

Wilson ( 1986) Bosma et al (1992) Itty (1992) (E) Agyemang et al. ( 1994) Itty (1992) (E) Gryseels (1988) (C) Mukasa-Mugerwa ( 198 1)

Zebu Bos.t. Bos.t. Crossbr.

Itty (1992) (E) Itty (1992) (E) Itty (1992) (E) McDermott et al. ( 1993) ; Gitau et al.

Bos.t. Bos.t. Bos.t. Several Zebu Zebu Zebu

ILCA (1979) Hoste et al. ( 1992) Feron et al. (1988) Semenye and Chabari (1980) Dolan (1994) Trail et al. ( 1985) Haile-Mariam et al. ( 1993)

Crop-livestock SA SASHSH HL HL Smallholder SH SH SH HL Ranches SA-SH SH SSA SH SA

farmers with livestock Kenya Togo Zaire Kenya

W. Africa W. Africa Zaire Kenya Kenya Tanzania Ethiopia

Zones: A, arid; SA, semi-arid; SH, subhumid; H, humid; I-IL, highlands. C, comprehensive household surveys; E, economic analysis. Best., Bus taurus, e.g. trypanotolerant breeds. Z, zebu; crossbr. are exotic Bos taurus and their crosses with indigenous

Rege et al. (1993a.b)

( 1994a,b,c )

or Sahiwal zebu.

marketing (Table 2) were also collected to provide a more thorough diagnosis of constraints, opportunities and future system viability. Occasionally, these diagnostic phases have been followed by the testing of interventions in on-farm trials (e.g. hay-making and feeding to calves (Coppock, 1991) and anthelminthic drenching of small ruminants (Peacock, 1984; Bekure et al., 1991)). Except for specialist ranching systems (e.g. references listed in Table 3)) monitoring procedures for most livestock systems in SSA are usually holistic, in which disease and other factors influencing productivity are assessed within the overall production system.

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Table 4 Examples of productivity

monitoring

studies for sheep and goats in sub-Saharan

Zone

Country

Reference

SA-A

Kenya Kenya Burkina Faso Mali Mali Swaziland West Africa Senegal C&e d’lvoire Nigeria Nigeria Kenya Ethiopia

Peacock ( 1984) Wilson et al. (1985) Wilson ( 1987) Wilson ( 1986) Bosma et al. ( 1992) Lebbie and Manzini ( 1989) Thiry et al. ( 1993) Faugem et al. (1990) Ambruster and Peters ( 1993) Sumberg and Cassaday ( 1985) Bosman ( 1995); Ayeni and Bosman (1993) Semenye and Hutchcroft ( 1992) Mukasa-Mugerwa ( I98 1)

SA SA SA SA-SH SA H SH-H H HL HL

Zones: A, arid; SA, semi-arid;

Africa

SH, sub humid; H, humid; HL, highlands.

For example, levels of health care will depend on production goals: where milk sales provide substantial income, female calves and heifers receive preferential treatment (Gitau et al., 1994b,c), whereas male calves are favoured when they are regarded as future oxen for traction as is the case in the Ethiopian highlands (Gryseels, 1988) and in the cotton belt in francophone West Africa (de Leeuw et al., 1995). Hence, multi-purpose output and costbenefit analyses are required that include tangible outputs (milk, live animal sales, hides and skins sales, manure (dung and fuel) and traction) and less tangible values such as investment value (hedge against inflation and a source of ready cash in emergencies) (Table 2).

5. Development

of monitoring and assessment methods

Given the multitude of livestock systems and monitoring interests, a wide variety of methods have been used (see references in Table 3 for cattle and Table 4 for small ruminants) . Nonetheless, efforts have been made to improve and standardise methods: Murray et al. ( 1983) outlined methods relevant to impact assessment of trypanosomiasis in livestock systems in tsetse-infested areas, while FAO ( 1984) produced a manual for ticks and tickborne disease control. ILCA ( 1983) suggested methods to assess labour constraints, income and expenditure and marketing in (agro-) pastoral systems. Later, ILCA ( 1990) developed a more comprehensive manual covering most variables listed in Table 2. To diminish the bias towards cattle, Wilson ( 1990) described methods to monitor small ruminant productivity. More recently, large-scale multilocational and longitudinal monitoring of flocks has been on-going in Senegal (Faugere et al., 1991) and Zimbabwe (Monicat, 1991). Data storage and analyses are computerised and include ‘modules’ on different categories of diseases (respiratory, reproductive), causes of death and follow-up tests (e.g. faecal analysis, serological tests). The modules can then be linked interactively

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with other productivity modules (e.g. growth, body condition and reproductive performante). As the need for on-farm trials to assess interventions was recognised, Amir and Knipscheer ( 1989) focused on trial design and methods of analysis of biological and economic performance. To encourage NARES scientists in SSA to set up both diagnostic and intervention monitoring systems, ILCA organised numerous training c,ourses. These and other efforts sought to improve the technical quality of monitoring efforts, providing methods that delivered data justifying statistical analysis and producing research results that would withstand peer-review. Such methods are essential for rational livestock planning. However, the technical demands and length of time required for such monitoring inhibited farmer participation, encouraging non governmental organizations (NGOs) and others to explore less rigorous and more rapid approaches to mobilise and sensitise unalphabetised target groups. These rapid and often participatory rural appraisal techniques (PRA) have evolved in recent years. They aim to foster bottom-up participation of rural communities and usually have a farming system perspective placing livestock as an integral part of the enterprise mix of the target groups. The major features of available natural resources are captured by key informants mapping the soil and vegetation types, infrastructure, mobility patterns, ethnic and social community structures, in their own locality. Semi-structured interviews and guided dialogues with randomly selected informants are used to elicit supplementary information on indigenous knowledge on range resources, veterinary and husbandry practices and descriptions and conceptualisation of livestockdiseases (e.g. Stem and Sollod, 1994). Details of the livestock sub-system are elicited by the recording of female progeny histories of herds and flocks and seasonal calendars of mobility, feed resources and disease incidence. Ranking techniques, such as proportional piling (of stones or beans), have been used for assessing the impact of animal diseases, the merits of range species and their uses, the historic analysis of drought impact and severity and the relative importance of different activities on income ( ‘livelihood analysis’). At the village level, wealth ranking of households by key informants has also been found useful (Grandin, 1988). These and other PRA approaches for pastoralists have been assembled and reviewed recently by Waters-Bayer and Bayer ( 1994). In many instances, PRA methods have been effective in eliciting local knowledge, involving local people in planning and thus increasing their commitment to development activities. The development of specific monitoring systems to assess disease impact have varied with the livestock system of interest (e.g. Traore and Wilson, 1988). In sedentary croplivestock systems, standard methods to account for the cost of drugs and other health care inputs combined with mortality rates and informant data on causes of death provided a preliminary assessment of the impact of disease on livestock output (Itty and Swallow, 1994). However, in arid and semi-arid zones, due to the overriding effect of rainfall-related starvation and death, disease as a single cause of morbidity and death has often been difficult to isolate. In a number of areas of SSA, the assessment of trypanosomiasis impact on livestock production is of particular importance. Most common, primarily in West Africa, have been monitoring studies on the relative performance of trypanotolerant Bos raw-us cattle (Itty, 1992). Biological productivity was monitored together with cost and benefit estimates in different locations to assess the economic merits of trypanotolerant breeds (see reference

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list in Table 3). Where such direct measures were not available, parallel observational data on the effect of trypanosomiasis on productivity variables for traditional systems has been collected by a number of researchers (e.g. Landais (1983) in Cote d’Ivoire; Thiry et al. ( 1993) in the Gambia and Rowlands et al. ( 1994) in Ethiopia). Likewise, detailed longitudinal studies have monitored the relationships between trypanocidal usage (preventive and curative), temporal PCV and other parameters expressing trypanotolerance, and productivity measures such as growth rates, mortality and reproductive performance in well managed ranches (e.g. Trail et al. ( 1990) in Zaire and Gabon; Dolan ( 1994) in Kenya). For small ruminant systems, disease monitoring has mainly been conducted in higher rainfall areas. Village surveys showed that mortality in sheep and goats was an overriding constraint, much of which was caused by the rinderpest-related viral infection, peste de petits ruminants (PPR) (Sumberg and Cassaday, 1985). Subsequent development and delivery of a vaccine was monitored and PPR incidence was significantly reduced with concomitant increases in performance and profitability (Ayeni and Bosman, 1993). Monitoring of disease impact on small ruminant production has received increased attention in recent years (e.g. Lebbie et al., 1993).

6. Monitoring for specific livestock production systems

6.1. Pastoralists In African pastoralist systems, the scope for monitoring is limited. This relates both to the difficulties of collecting information and transporting samples to laboratories from highly mobile herds. Movement is central to survival and traditionally pastoralists have monitored their orbital environment to support movement decisions. Examples of traditional monitoring activities include scouting of rangelands and water supply (e.g. McDermott and Ngor, 1984) and surveillance for potential trypanosomiasis challenge (Leak et al., 1988) and contagious disease outbreaks (Schwabe, 1984). What are the information and decision needs to be served by monitoring systems for pastoralists? Pastoralist herders are usually more focused on livestock survival than on productivity. However, survival options for pastoralists are more constrained. Pastoralists are less isolated than before and thus traditional monitoring systems for rangelands, water sources and disease occurrence to guide herders’ movement need to be augmented by environmental, land use and other information. Since the land areas of pastoralists are constantly being eroded, government and pastoralist leaders have an important responsibility to obtain information on potential mass mortality due to drought and contagious diseases, grazing rights and local control and management of resources to protect the interests of their pastoralist constituents. A combination of monitoring approaches is required. Both short-term and longer term research and development objectives need to be considered; often animal health initiatives are an initial priority for herders but issues of land utilisation and environmental changes are proving crucial to pastoralist communities in the medium and longer terms (Scoones, 1994). Participatory approaches are essential to mobilise community participation in data gathering and decision making (Waters-Bayer and Bayer, 1994). However, a number of

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potential constraints against and opportunities for improving livestock production may either be unrecognised or misinterpreted by pastoral&s. Thus, participatory approaches need to be combined with well designed epidemiological and ecological studies to estimate baseline production and health, assess potential constraints and test proposed interventions under local conditions. A useful iterative framework for combining these approaches is described by Stem and Sollod ( 1994). In many instances, broader interests than livestock need to be considered and the collection of information on human health and nutrition and other data can be incorporated into livestock monitoring systems (Swift, 1984). The methods needed to collect information for monitoring pastoralist systems need to be diverse and adaptable depending on movement patterns and distances. For more mobile and isolated pastoralists, innovative techniques to incorporate pastoralists into both service provision and monitoring are essential. One example of how traditional livestock experts (atet) from the pastoralist Dinka of southern Sudan could be utilised has been detailed by Schwabe and Makuet Kuojok ( 1981). Information gathering in the larger environmental system has been greatly enhanced by the recent and rapid development of technology supporting geographic information systems (Coughenour, 1991). However, much thought needs to be given to how such information could be integrated into decision support systems for governments and pastoralists (Scoones, 1994). 6.2. Smallholder

d&y farmers

In high potential farming areas especially in the east African highlands, smallholder dairy farms provide much of the milk supply (Gitau et al., 1994a). In this system, the scope for monitoring is much greater. Currently, there is limited data on milk sales, income from milk (Walshe et al., 1991) and other commodities (broilers, pigs) available in regions with formal marketing organisations. In some areas, health and production indices and factors influencing those indices have been estimated (e.g. Gitau et al., 1994b,c). In most areas there are also routine passively collected data from veterinary department treatment records, dip tank attendances and in a few areas even artificial insemination records. However, in most areas (southern Africa being a notable exception) these passively collected records usually reflect the activity of the government department concerned more than the actual level of production or disease occurrence in the field. What are the information and decision needs to be served by monitoring systems for smallholder dairy farmers? In addition to establishing baseline health and production levels there are a number of monitoring needs of different client groups. First of all, it is important to assess variations in health and production indices (Holden et al., 1993; McDermott et al., 1993) to determine if some farmers are more successful than others. Such information demonstrates the opportunity for increasing production under local conditions and is of interest to farmers, farmer cooperatives, government extension&s and agricultural research groups. Farmer cooperatives and other government and research organisations also require information on the economic success of extension and cooperative society inputs and on marketing options to maximise returns on product sales. There are a number of monitoring mechanisms that could provide useful data. At the cooperative level, routine collection of data from dairy cooperatives on milk output by farm, use of inputs (e.g. feed, credit, breeding and veterinary services) and actual and projected

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milk output by cooperatives would be important to help plan milk marketing strategies and the provision of input services. Any monitoring system by cooperatives must also include periodic (annual) polls or surveys to assess farmers’ opinions on the services provided by the cooperative and how they could be improved. At the farm-level, periodic (every 5-10 years) well designed animal health and production studies (e.g. McDermott et al., 1992; Gitau et al., 1994a,b,c) need to be conducted on randomly sampled farms to detect changes in production practices, production levels and disease occurrence. Once interventions are developed based on these and other studies, on-farm trials are required to test them under local conditions. The development of production and health indices to be used in monitoring need to be carefully considered and standardised. These indices will need to be adapted from standards such as those developed elsewhere (e.g. Fetrow et al., 1988). For example, herd calving rate (a useful reproductive index for larger farms (PAN Livestock Services, 1990) ) is far too variable for small farms with one, two or three cows (Odima et al., 1994).

7. Contributions

of livestock monitoring in SSA

Although the impact of more than two decades of monitoring is not easy to gage, if we assume that published and verbal communications do have impact, then the effects are likely to be two-pronged: a narrow one of better defining the productivity levels attained in traditionally managed production systems and a wider impact on the perceptions and views of the ‘clientele’ about how livestock producers operate, their goals, constraints and welfare. The monitoring of cattle productivity in traditionally managed herds across a broad spectrum of systems has provided a baseline of what output to expect from cattle and small ruminants that derive their feed primarily from natural pastures and crop residues. Although variables such as calving rates, milk offtake and calf growth and mortality rates differ, when aggregated in a cow-calf productivity index, most cow outputs lie in the range of 20-25 kg of weaned calf per 100 kg of cow year-‘. Growth rates of immature stock are also fairly uniform averaging 50 kg per head year- ’ and explain why the age of first calving differs little between systems from 3.5 to 4.5 years in smaller breeds to up to 5 years in the larger zebu breeds (de Leeuw and Wilson, 1987; Agyemang et al., 1994). Breed effects are more difficult to measure, as breeds are confounded by locations and systems with zebus predominating in the more mobile systems in the drier areas and trypanotolerant breeds (N’Dama, Baoule, etc.) being common in wetter areas with measurable levels of tsetse challenge and trypanosomiasis risk. Extensive research in the Gambia has shown that, under comparable levels of management, the performance of N’Dama cattle equals that of zebu (Agyemang et al., 1994). However, production costs may be lower because of lower expenditures on drugs in N’Dama herds. To what extent local systems perform below potential has been deduced from best versus worst herd comparison mainly in terms of cow-calf performance. On average, outputs were 20% above and below the mean, indicating that within the same environment productivity is influenced by herding management, calf rearing practices, disease outbreaks and other more intractable factors. Yardsticks for breed potential can also be derived from cow productivity data from well managed ranches and research stations. In these settings, cow-

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calf productivity is found to be mostly in the range (see references in Table 3) of 35110 kg of calf 100 kg-’ of cow year-’ because of the combined effects of higher calving rates, lower calf mortality and calf growth. Despite the early weaning (at 7-8 months) practised in ranches, calves weighed over twice as much ( 160-l 80 kg) as late-weaned calves (7090 kg) in traditional systems where cows were milked. Similar comparisons have been attempted between on-farm sheep and goat breeds and those on research stations. Wilson, ( 1991) summarised the available information on 20 goat and 25 sheep breeds in SSA (see references listed in Table 4)) listing their performance in actual production systems and/or on research stations. An important contribution of monitoring studies in SSA (Tables 3 and 4; Rey and Fitzhugh, 1994) has been to change perceptions and old stereotypes. By the end of the 1980s ‘irrational’ pastoralists had become rational entrepreneurs facing the challenge of non-equilibrium environments where opportunistic exploitation of variable resources mitigates risk and enhances household survival (Behnke et al., 1993; Scoones 1994). Donor attitudes have changed, so that solutions grafted on western ideas such as managed beef production have lost credence, and instead, the multi-goal strategies of pastoral producers are more likely to be incorporated into the design of development projects. Broad monitoring efforts have also raised awareness of the problems faced by livestock farmers: thus, stimulating a push for problem-oriented action to increase agricultural production (Fitzhugh et al., 1992). This has influenced NARES to re-direct their training and research towards the testing of problem-solving interventions on farms. This shift in research orientation has also begun to have an impact on the attitudes and priority-setting of veterinary, livestock production and range management departments. Often, personnel from these departments have been co-opted in surveys and monitoring projects, which has broadened their exposure to and awareness of the problems, constraints and opportunities faced by farmers (Thorpe et al., 1993). What will be the future monitoring needs in SSA? For pastoralists and agro-pastoralists, we anticipate that the current emphasis on resource and participatory monitoring will remain, but, that with time, changes in production goals will alter these traditional needs in some areas. For example, production efficiency may become more important and then potential increases in weight gain due to strategic deworming or reproductive performance by controlling brucellosis (McDermott et al., 1991) may be of more interest. In such areas, market information on supply, demand and prices will also eventually be required. For crop-livestock and specialised livestock systems in higher agricultural potential areas, we expect both increasing intensification and specialisation of livestock enterprises. This will require both increased use of feed, labour and health care inputs and higher outputs and income. Increased husbandry and disease control expertise will be required to ensure sufficient returns to investments in breeding stock and housing and to safeguard these investments with better disease control. Fortunately, the health and production monitoring systems already developed (Radostits et al., 1994) should be easily adaptable and are likely to be integrated into contractual arrangements between specialised commercial units, such as feed companies or meat processors (Winrock, 1992). Comparable intensification and specialisation trends are also likely for smallholder dairy producers in the east African highlands (Walshe et al., 1991). Monitoring systems for such smallholders, as described above, will require more adaptation. Constraints are likely to be

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multi-faceted (e.g. breeding, feeding, health care) and production improvements will require close integration of both health care and management inputs (McDermott et al., 1993). The packaging and management of livestock health and production information for decision support remains undeveloped in SSA. This is likely to change as information and decision support systems are developed or adapted from systems designed for other locations (e.g. Sanson et al., 1991; Richardson et al., 1993; Bernard0 et al., 1994; Jalvingh et al., 1994). This should be a priority. While there are undoubtedly many gaps in the information on livestock health and production in SSA, we believe that the greatest needs are in managing

the considerable amounts of data already available.

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