N. O. NIELSEN
University of Guelph, Guelph, Ontario, Canada NIG 2W1
The roles of livestock in agricultural economy, culture and ecology are complex and vary according to specific contexts around the world. Several authors, including those of the background report for this conference, have identified and discussed many of these roles, and it is not our intent to recount them (Steinfeld et al 1997). It is widely recognized in these discussions that livestock are not raised for their own sake, but to meet interacting, and sometimes conflicting, human nutritional, economic and environmental needs. For instance, as part of an IDRC-funded research project on human disease problems associated with intensive livestock slaughtering practices along the riverbanks in Kathmandu, it has become clear these cannot be seriously dealt with without also addressing issues of community empowerment, rural-urban migration, globalization of the economy, energy and water use for non-agriculturally-related activities, and changes in nutritional habits and culture.
Having said this, it is also clear that there is a paucity of conceptual and methodological tools to do the inter- and transdisciplinary work necessary to address such complex interactions. Agroecosystem health represents a theoretically and practically coherent approach to research and management of the full range of issues - from human nutrition and health to economic adaptability and ecological integrity - which must be addressed if workable policies and management strategies incorporating livestock are to be developed. Drawing on a diverse body of systems and management literature, and building on experience related to veterinary herd health management and human population health and healthy communities, agroecosystem health pulls together research and management into a seamless process of sustainable learning and adaptation.
Agroecosystem health - the concept
Agroecosystem health management comprises at least five (not necessarily linear) steps: 1) a description of the agroecosystem in systemic terms; 2) identification of decision-makers and/or stakeholders; 3) establishment of goals, that is, perceived attributes of a healthy system, operational objectives related to those goals at various scales and time horizons, and determination of measurable indicators which will give information about whether or not those objectives are being achieved; 4) identification and implementation of desirable and feasible changes, which often involves resolving conflicts among goals set by different decision-makers at different levels; and 5) monitoring of the selected indicators, and adapting to changing circumstances or unexpected or undesirable outcomes. This may mean revisiting the description of the system, the objectives selected, and the management options chosen.
Agroecosystem health management should be distinguished from what one might call agroecosystem medical practice. While diseases and dysfunctions, the focus of medicine, are important both as stressors on the system and as indicators of system dysfunction, they are not in themselves the focus of health management. Medical practice, responding to specific problems, requires analytic and diagnostic skills in support of expert decision-making, assuming a stable systemic context. The intent is to identify what is undesirable and fix it. Health management, responding to a situation in which multiple problems and opportunities are connected in a web of interactions, is an integrative activity which draws on an understanding of historical development and desired futures to facilitate adaptive decisions about overall system management. The intent is to identify what is desirable and enhance it.
The application of health approaches to issues of environment and economy in agriculture enables us to draw on a strong tradition of dealing with the integration of science and practical management. Although the application of health concepts to the multi-level complexity of agroecosystems presents some unique challenges, those of us who have worked with health and disease in individual animals, herds, farms and communities, do not see these as being insurmountable.
The great strengths of applying health ways of thinking to agroecosystem evaluation are that it requires: 1) integration of the biophysical and socioeconomic dimensions of the problems being investigated, from nutrition and food security, to education and empowerment of women, to the protection of watershed integrity; 2) integration of research and management, which are viewed as being part of the same process of intervention and evaluation; and 3) bridging analytical/ diagnostic (medicine) and integrative (health management) issues, where particular problems are re-interpreted in systemic terms. Furthermore, the language of health is a language of public discourse which enables us not only to bridge the gap between science and management, but to involve the public we serve in the definition and resolution of these complex socio-ecological issues whose scope is clearly beyond the expertise of any particular group.
Agroecosystem health management: the practice
1. Describing the system
Agroecosystems are inherently multi-level. Fields are nested within farms, which are nested within rural communities and sub-watersheds, which comprise larger watersheds, bio-regions, and so on. This kind of a nested hierarchy has been called a holarchy, and the things which are nested are called holons. This provides a general terminology for talking about these kinds of systems. These holons, having definable boundaries, are interdependent at each scale and across scales. They are thus both necessarily bounded and leaky; indeed, one management goal of agroecosystem health is to maintain adequate boundaries without stifling interchange. This holarchic view of agroecosystems has become widely accepted as it is recognized that farmers make decisions in particular contexts, and that those regional contexts must be defined and managed in such a way that appropriate decisions can be made at the local level.
Any particular level in an agroecosystem may be viewed externally or internally. An agricultural community, may be viewed in terms of its internal needs and dynamics, or in terms of its relationships with the larger region in which it is situated.
For example, colleagues who are working with us on a joint CIAT-University of Guelph project on complex systems approaches to tropical agroecosystems (Rowley et al 1997) have identified important questions with regard to in- and out-flows of useful energy, materials and information. This is an external view, enabling us to study, for instance, the steepness of the gradient of useful energy across the system, that is, the size of the difference between inputs and outputs at farm, community or national levels. This enables us to identify whether this system is dependent on massive inputs, one measure of capacity to respond to future stressors.
By looking internally, we are able to determine how various operational objectives (for instance, minimization of risk, maximization of income) and activities to achieve those goals, (rotations, mixed systems, contract selling) can, or might, contribute to the development of sustainable, self-organizing structures in the local ecosystem. That is, are economic activities related to natural resource use contributing to the build-up of local capital? Once this is described, we can begin to look, for instance, at how various livestock roles affect these structures.
By exploring the holarchy within which these activities take place, one can begin to delineate temporal as well as spatial constraints, opportunities and the costs of change. For instance, income may be generated daily, at a household level, from livestock slaughter, but cumulative negative impacts on water quality may take a generation to accumulate at a watershed level, with catastrophic consequences. Individual farmer bankruptcies may appear as “noise” when measured in terms of national trends and averages, but may be tragic for individuals and families
Another way to assess agroecosystems externally at a particular level is to create attractor models in several dimensions. This is based on the observation that many socio-ecological systems fall into a few patterns of behaviour and resist pressures for change. In some cases, these appear to represent what my colleague Gilberto Gallopin of CIAT has called “perverse resilience”, leaving communities in states of economic stagnation and environmental degradation despite our best efforts. In other cases, agroecosystems appear to resist such degradation. If conceptual models of such attractors can be created, we can begin to identify their determinants. These are similar to what have been called determinants of health in the population health literature.
2. Identification of responsible decision-makers and stakeholders
Agroecosystems may be described in terms of at least two different kinds of holarchies: a biophysical one (animals, herds, subwatersheds), and a socio-economic one (individuals, families, communities, and countries). This is problematic, but not fatally. In most real world situations, some practical accommodations can be made which allow one to envisage the system in terms of the particular holarchy which is most important for decision-making on a particular set of issues. In most agroecosystems, farms and rural communities tend to represent important levels of decision-making with regard to both ecological and socio-economic issues.
In order to successfully implement an agroecosystem health management program, one must have a reasonable idea of power relationships within and across levels. Herd health programs have been remarkably successful because there is a well-identified manager who can set goals. At the community and regional levels, issues of governance are more problematic.
Institutional and stakeholder analysis can be carried out to determine who should be at the table, and how to involve them while recognizing political and economic power differentials.
Once the appropriate participants are recruited, participatory action research methods can be employed to facilitate the articulation of appropriate goals and objectives, given the constraints and opportunities identified through research. In many cases, conflict resolution and negotiation skills and multi-objective programming expertise may facilitate this process.
Some researchers have found influence diagrams, or signed diagraphs (Caley & Sawada, 1995) to be helpful. These identify feedback loops which re-inforce or weaken particular system states, and clarify who has the power to influence those connections. In these diagrams, which some have termed “spaghetti diagrams”, various components of the system are connected by arrows which are labelled as positive if they co-vary in the same direction, or negative if they co-vary in opposite directions. For instance, a line between income and meat-eating might be positive, while that connecting water quality with human disease would be negative. By examining these diagrams one can determine whether particular relationships are likely to be amplified or dampened when changes are made; when time-lags are considered, one can determine whether to expect stabilization or oscillation of patterns. In the context of such diagrams one can begin to understand why, for instance, the education and empowerment of women might have a greater long-term effect on the health of agroecosystems (both directly through increasing available knowledge to the system and indirectly by decreasing demands on the system through self-directed population control) than technological interventions which may appear to be more attractive in the short run.
In some cases, new organizations can be created to bridge economic or political jurisdictions. The International Joint Commission for the Great Lakes is one such example, but there are many other economy-environment round tables and non-governmental multi-stakeholder groups that have emerged throughout the world in the past few years, at levels ranging from local communities to the biosphere.
Whereas one branch of agroecosystem health management is based on a scientific description of the system, this cannot proceed without reference to the other branch, the articulation of what kind of system is considered to be desirable by decision-makers and stakeholders (Boyle et al 1996).
3. Setting goals and operational objectives, and selecting indicators
Having set out a holarchy and several dimensions, one must derive some criteria by which one may judge health. Most definitions of health combine a notion of a harmonious balance (measured in terms of the current functioning of the system) and the notion of capacity to achieve some goals (often measured in terms of various forms of social, economic or natural capital) (Waltner-Toews & Wall 1997). In general terms, one may ask the question: are the quality and quantity of internal and external resources sufficient, and is their organization appropriate, for the agroecosystem to meet its goals (Waltner-Toews & Wall 1997)?
Since agroecosystems are human re-arrangements of ecological systems, these goals are fundamentally human ones reflecting a desire to enhance the quality of life for ourselves and our descendants. Even the desire to maintain biodiversity can be seen as a way of protecting future options for human community development. In general, one moves from articulating general goals, to setting operational objectives, to selecting measurable indicators which can be used to assess progress.
Some of us have found it useful to place our various research and management activities into a cubic framework, with axes representing scale (farm, community, region), dimension (biophysical, social, economic) and health goals (equity, quality of life). With this as a starting place, we can begin a more rigorous process of identifying within and across scale contradictions and possible goal conflicts.
What emerges from this combination of holarchic system description and goal-setting by decision-makers is a process which incorporates the participation of farmers, communities and regional governing organizations in defining and monitoring the health status of the system of which they are a part. Because the capacity to adapt to unpredictable future changes is an essential part of health, and local empowerment is an element in this capacity, selection of indicators a priori by outside experts is counter-productive. The operational objectives which reflect agroecosystem goals, and indicators which measure their achievement, can only be identified through a process of negotiation among those who live in and/or have a stake in the health of those agroecosystems.
The role of researchers and agroecosystem health practitioners in this context shifts from the conventional view of experts giving advice, to that of facilitators helping to explore the possible consequences of alternative choices.
Based on the models used to describe the agroecosystem, communities may be able to better identify programs whose indirect effects are more beneficial than programs designed around more obvious, short-term, direct outcomes. For instance, the occurrence of malaria in northern Honduras and of parasitic zoonoses in Kathmandu might both be functions of inappropriately simple policy goals related to increasing income through agricultural production. On the other hand, some resource-poor communities have survived major stresses because they have been able to translate even minimal economic activity and available natural resources into building up a crucial third variable - local social and economic capital. The use of cover crops to feed livestock in mixed farming systems in Central America may have implications for relationships between men and women in families, between national goals for increased cash cropping versus local goals for food sufficiency, and between low-priced American corn and traditional corn-cover-crop systems.
In all these cases, the complex feedback loops identified in the models may help to guide intelligent, multi-level management programs and policies with verifiable outcomes.
Nevertheless, all of these methodological tools are merely aids to better understanding and more intelligent decision-making. They do not lead to expert knowledge and control, but to a more deft handling of uncertainty and change.
4. Implementing desirable and feasible changes
In conventional herd health or community health programs, the articulation of goals and objectives is seen to represent the transition from research to management. Science is descriptive and goal-neutral. Scientists can describe several states for a given socio-ecological system, but have no basis for preferring one over another. Furthermore, because of the complex feedback loops over various temporal and spatial scales, and because people are inside agroecosystems, it is neither ethically desirable nor scientifically feasible to run controlled experiments which test single hypotheses.
For instance, one might define a hypothesis related to more efficient production of beef. This might lead someone to study economies of scale, concluding that these result in major cost savings to the producers. However, such systems, focusing on internal efficiency, lead to recycling of wastes within the system. On the one hand, this results in larger volumes of cheaper meat, albeit with high energy subsidization; on the other hand, this marginalizes more farmers, disrupts and often destroys rural communities, produces more large volumes of point-source waste, and creates unprecedented ecological opportunities for foodborne pathogens such as Salmonella spp, E. coli and prions.
Because hypotheses about agroecosystem health relate to the system as a whole, they are necessarily complex and multi-faceted. Patterns of self-organization to which the system is drawn are strongly determined by the goals and their implementation. With global markets, facilitated through road-building and transport changes, applying increasingly steep gradients to local agroecosystems, single-goal attractors are almost invariably fatal attractors. In seeking to maximize achievement of a single goal, all the unstated goals like equity, democracy and sustainability are critically undermined. Furthermore, there may be no stable optimal solution, but a series of approximations. 1
It is at this stage of deciding on appropriate management programs that it becomes necessary to facilitate negotiations between various decision-makers to accommodate goals that may be conflicting. The creation of platforms for negotiation (Roling, 1996) or other fora is thus an essential part of agroecosystem health management.
5. Monitoring and adaptation
The monitoring of indicators, reflecting goals and objectives set by decision-makers and stakeholders through process of negotiation informed by science, is the most feasible way to test agroecosystem health hypotheses. Management, in this context is research; management programs are essentially “natural” experiments which should be designed and monitored as rigorously as any laboratory experiment. Agroecosystem health management demands that decision-makers become part of the research process, and that new programs at various scales be formally implemented in a way that allows for monitoring and adjustment. By incorporating human communities into the research process, by negotiating trade-offs between multiple goals, and by making policy and management changes part of the research process, agroecosystem health management is simultaneously research and management. One is not left, in the end, trying to sell experimental results to recalcitrant farmers or policy-makers.
1 Whatever its faults, the Holistic Resource Management (HRM) program has recognized the centrality of setting social and economic as well as environmental goals and then devising management strategies to achieve those goals. While the specifics of the HRM process may apply best to individual large landowners in rangelands, the general approach is a sound one.
Agroecosystem health management, being both participatory and structured in a looping fashion which mimics the system itself, does not result in a single definable outcome. In this, agroecosystem health management is quite unlike a simple experimental approach which asks a simple question under controlled conditions and receives a simple answer, or industrial management, which may focus on a simple outcome such as producing more pigs more cheaply. This may be frustrating to those of us used to well-defined experiments and business managers accustomed to the stable world of the 1960s and 1970s. Many executives of multi-enterprise corporations, however, have already recognized the significance of similar approaches in devising adaptive strategies to a rapidly changing world. It is none too soon for public institutions to follow suit. The outcome of this approach is a sustainable web of learning organizations, from farms to communities to global institutions, which are capable of acting, monitoring and adapting in a world characterized more than anything by perpetual change.
The contributions of animals to a sustainable biosphere, whether positive and negative, economic, cultural or ecological, cannot be determined by looking at the animals themselves, in terms of livestock production systems or animal populations. The values of animals are determined by the ways in which they interact with the full, complex socio-ecological context in which they are found. Agroecosystem health management is a way to put questions related to livestock, the environment, and human needs into a larger context in such a way that human activities can be structured to the benefit of all.
The authors wish to thank the International Development Research Centre (IDRC, Ottawa), the International Livestock Research Institute (ILRI, Nairobi), the Centro International de Agricultura Tropical (CIAT, Cali), and the Canadian International Development Agency (CIDA, Ottawa) for their support for various aspects of this work. We are also indebted to our colleagues on the Agroecosystem Health Project at the University of Guelph (1993–1996) for several years of fruitful debate on these issues. More recently, these ideas have benefited from an international workshop at the CIAT in Cali Colombia in May 1997. Organized as part of the CIAT-University of Guelph agroecosystem project, participants included project researchers (D. Waltner-Toews, G. Gallopin, T. Rowley, E. Raez-Luna); scientific advisor James Kay from Canada; and other researchers from Canada (H. Regier, S. Slocombe, M. Boyle), Italy (M. Giampietro, G. Pastore), Peru (M. Ara, H. Guerra Flores, R. Labarta Chavarri, J. E. Musso Marcovich), the U. S. (C. Restrepo) and CIAT (R. Best, S. Fujisaka, E. Veneklaas, R. Knapp, F. Holman and M. Winograd)
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