CHAPTER 8

Making Sense
of Excrement’s
Wicked Complexity¹

The list of excrement-related problems is long and growing by the day: fecal-transmitted parasites in Nepal; excrement-associated foodborne disease outbreaks in Europe and North America; epilepsy and other neurological disorders, some of which are fecally transmitted parasite infections (recall the Toxoplasma and Taenia solium stories); nitrate pollution of water in the Netherlands; bacterially contaminated water in cities the world over. Also related (less directly, but still in demonstrable, substantial ways), food insecurity and famine in the horn of Africa and rapid, dysfunctional urbanization in most parts of the world are providing a justification for large corporations to centralize and globally trade both food and excrement.

The world seems to be tumbling out of control, and the old scientific, technical, and political agendas seem powerless — and lack the economic, moral, and intellectual resources — to respond effectively. We simply cannot set a priority of diseases and problems and, one by one, go down the list and get rid of them. The list is endless. Worst of all, the kind of solutions we devise to some problems — say, of food shortages — create as many problems, such as creating ideal conditions for emergence and spread of new diseases, as they solve. Treating animals for parasites may destroy the landscapes that support those animals.

At the core of the wicked mess of shit, food, and ecological sustainability is a challenge of theory. We have developed ad hoc solutions, using a Henry Ford, linear, industrial model of nature. This theory works in a factory, or in a laboratory, but wreaks havoc in the world outside those confines.

“Normal”² scientific (clockwork, industrial, linearly causal) assumptions about the world provide no formal way of integrating all the relevant pieces, or even to even ask the important questions. It is not an accident that shit and science have the same linguistic roots. How might particular solutions to food security affect ecological sustainability? How might certain solutions to manure management problems affect climate change or food security? How might some responses to veterinary or medical problems actually undermine long-term health? How do we deal with the grief that necessarily comes with change, no matter how important or “good” the change may be? Can science be “redeemed”? The answer to this last question is: yes, if we take a broader view of science as a way of generating knowledge grounded in the “real world.”

If we cannot set a list and solve the problems, one by one, what are we left with? In conventional social development and normal scientific terms, not much. Researchers do excellent, independent disciplinary work, based on what the philosopher of science Thomas Kuhn called normal science: a science where every discipline has its own rigid rules of practice, acceptable evidence, and quality control. The scholars then hand the result over to politicians, whom they expect to be much more thoughtful, insightful, integrative, and visionary than any university scholar. We then lament that the politicians make decisions using criteria based on someone else’s evidence rather than our own.

The policy makers, even the most thoughtful among them, even those for whom “One Health” (integrating the health of people, other animals, and ecosystems) is at the top of their agenda, are faced with the challenge of trying to integrate the social determinants of health, the environmental determinants of health, and their limited budgets. Manure management is competing with child poverty and maternal health and population control and disappearing whales and pesticide pollution and avian influenza and cholera and hunger and salmonellosis and childhood obesity and car accidents. The list, indeed, is endless, resulting in one plea after another for more money for more programs.

Although fraught with danger and uncertainty, the task is not hopeless, because, fundamentally, the individual problems are part of one big, wicked problem. If we can get our heads around that, we can start to come up with viable solutions. We are a pretty ingenious species.

Let us go back to some basics of science and knowledge. Scientists are hunters and gatherers. Instead of fruits and nuts, we track the scats of reality in a confusing, deep forest we call the world. We do not actually know the world; we perceive it with our senses — sight, smell, touch, hearing, taste. These inputs create a set of neural connections that function as an internal mental model of “what is out there.” This mental model determines our behavior, and our survival.

Sometimes individuals are wrong. Sometimes a person is psychotic, or their neural connections or biochemical messengers get mixed up, or they take a singular case to be of general applicability, or their culture biases them to see some things and ignore others. Sometimes an animal ends up in the wrong place at the wrong time because the landscape on which its brain connections were based has been changed. Mistakes can be costly. A prey animal could be eaten, or run over by a car, or fly into a wind turbine, or a person could eat food or drink water contaminated by feces that contain cholera or E. coli organisms, or the markets for which swine farmers have been raising pigs might suddenly disappear because of public panic over a new strain of influenza.

We overcome these deficits by sharing information, by critiquing each other based on our perceptions, by telling and hearing our different narratives that we use to make sense of the world. “Based on my experience,” we might begin to say, or “based on this study we did.” This is no more, nor less, than a hunting story told around a campfire, a way of constructing meaning from facts.

Reality scat-gathering is only a small part of science. Building meaning around the facts, in a collective, open manner, is what differentiates a scientist from a junk collector. In this complex and uncertain world, good science is a systematization of the process of storytelling about perceived facts. Good science, the best science, is a way to share experience, to offer alternative explanations, to project future possibilities based on past experiences.

What does this mean in practice? The universe in which we live is characterized by a very rich set of connections, and what we see around us is open to a wide variety of influences from its surroundings. Some mathematically inclined complex systems theorists believe that complexity can be explained and “re-created” virtually using a few simple calculations that repeat themselves. However, most of us who work with complexity as it relates to addressing public health and environmental problems would challenge that assumption. Quantitative modeling can provide some interesting insights into the spread of a disease or the movements of nitrogen in the soil. However, modeling the complexity of the world — particularly if we include that most troublesome species, ourselves — in any comprehensive and definitive way is impossible. John L. Casti, who has written extensively about complexity research, calls it the “science of surprise.” If one takes this position, then only by accommodating many different perspectives can we begin to gain insight into some of the surprising ways in “how the world works.”

In practice, the complexity we see in the world is a function of the nature of the world itself, us who observe the world, and the questions we ask. If we ask how to fix a broken watch, or how to collect a stool sample from a dog, we can think of the watch or a dog in fairly simple mechanical terms, and we do not need to invoke notions of complexity. If we ask about the function of watches in society, or the social, political, economic, and ecological relationships required to acquire the resources, materials, and skills necessary to build a watch, we need to invoke complexity. Similarly, if we wish to save people dying of cholera, we have the relatively straightforward, albeit challenging, task of providing them with potable sources of fluid replacement. If we wish to prevent cholera epidemics, we are faced with complex, interacting political, social, economic, biomedical, and ecological forces.

How do we wiggle some space here to make important, often urgent, decisions? For practical purposes, we can take some key sets of relationships, look for basic principles or tendencies, and make at least reasonable projections as to outcomes, given certain inputs. Once we have tried something, we ask, did we see what we expected? In doing this, we are both engaging in systems thinking and simplifying the world in important ways. We should never confuse our models — however complex they may be — with the complexity of the real world. The only way to begin to approximate an understanding of the real world is to bring together as many perspectives as possible and try to gain a collective picture. Again and again.

If we think systemically about the world, it seems reasonable to propose that everything is connected, and that therefore everything we do has unintended consequences. However, not all things are connected or related equally: relationships have different strengths, and sometimes the links are spread widely across space and time. For instance, the choices European and North American consumers and farmers made with regard to increasing food supplies after World War II have had a vast array of unintended social and ecological consequences, many related to creation and disposal of manure. These consequences were only apparent in hindsight. Few would have predicted today’s world based on what people observed fifty years ago.

How then do we parse our thinking about the world systemically so that it becomes useful to us? First of all, we can generally classify our thoughts about systems into three groups: simple, complicated, and complex.

If I arrive in an emergency room after a car accident, I want to be treated by experts who know what kinds of fluid replacements to administer, how to insert a needle into a vein, how to fix a broken leg, and so on. If there is a spill from a livestock manure-holding lagoon, I want to engage good engineers who understand how to fix the spill as soon as possible. Drawing boundaries around these problems and thinking about them in fairly simple terms is the quickest way to solve them. I don’t want the physician in the emergency room to ask me about my life’s goals.

From a scholarly point of view, we can improve our understanding of simple systems by gathering more knowledge and developing good, relatively simple models. Practically, we seek good education and training, we want a hierarchy of command, and efficiency is good. We need to remember that this “simple system” version of a body’s condition or a manure spill is a function of the questions being asked and the problems we want to solve. In the face of an emergency, or even when a computer or a watch needs fixing, asking about the meaning of life or the role of technology in modern life is not helpful. Simple system views are starting places for asking questions. For a publically engaged scientist, they are never places to end.

Some issues evoke a more complicated systems view than fixing a watch or a bone. For instance, I can create mathematical quantitative models that predict that, if I do certain things in a certain way, I can land a craft on Mars, or dispose safely of certain amounts of manure on a piece of land with known soil type and in an area with relatively stable rainfall. Actually, I can’t really do that. More to the point, I can find experts who can. Working with complicated systems is highly expert-reliant. Because the mathematics and modeling are difficult — because there are so many relationships we are trying to keep track of — we need redundancy. We need to ensure that there are checks, balances, and options for Plans B and C.

Good education and training are important for tackling complicated problems. However, unlike for simple systems, effectiveness (achieving goals) is more important than efficiency. It was more important to actually land the Curiosity on Mars than to get it there as fast as possible using the least amount of fuel (although that was obviously one of many issues involved).

If we assume that the world is relatively stable, then we can imagine a great many problems to be solvable using complicated, multi-expert thinking. The planets and their gravitational forces were not likely to shift radically during the voyage of the Curiosity. In a reasonably stable climatic and political climate, biological diversity in farming or a mix of health-care delivery personnel in a medical system offer buffering. Redundancy gives the system some resilience in the face of change and stress.

Unfortunately, our best systems of checks and balances break down if the world becomes unstable. In the face of rapid climate change and political and economic instability, we are hard pressed to predict which crops will grow well, what the requirements for health care delivery might be, and which manure management systems are best. Indeed, in a world of incredibly diverse ecosystems and cultures, that complicated systemic thinking provides poor guidance even if the world is relatively stable.

As the context we live in becomes unstable, and as we move away from the illusion of a one-size-fits-all world, the problems we see as complicated are rapidly transformed into complex challenges. This is particularly true in city planning, agricultural and food systems, and the manure problems associated with them. Economies of scale (for both food production and manure disposal) make efficient use of certain kinds of resources under stable economic and environmental conditions, but are very brittle in the face of change. If everyone is growing corn, and the price of fossil fuels goes up, or the market for corn collapses, the system cannot adapt. People might go hungry because all the corn is used for fuel or, conversely, because they can’t sell their crops.

Large slaughterhouses that require high through-put of animals have had to shut down completely in the face of border closings or sudden changes in market access (due to BSE, or foot and mouth disease, or fluctuations in the price of oil). This can have cascading, devastating effects as farmers cannot even service local markets.

Suddenly we have shifted into a disorienting world where many of our predictive models are not helpful. We are like polar bears lost in a tropical desert. We are like fastidious office workers up to our necks in shit. This is when we need to think about complexity.

Complex systems are descriptions of complexity — attempts to describe the world as we live in it and experience it. Precisely because we are trying to understand incredibly tangled and unstable relationships, there are many such descriptions, or models, possible; different observers will see different things in the world and model them differently. Although mathematical models are useful to explain certain events (such as pandemics, climate variability, or the ecological and climatic impacts of manure creation and disposal), there is no single mathematical model that can pull all of these together with human behavior and allow us to predict what will unfold in the future. Raising a child, for instance, is not like sending a landing craft to Mars: it is much more complex and difficult. Managing a sustainable food and shit system or land use in a watershed where industry, human settlement, wildlife, and food production are vying for space is similarly complex.

Complexity theory has many facets, and it is not my intention to explore all of them here. I am particularly interested in those that might help us address the wicked problem of excrement. These include some basic elements of systems thinking (that is, looking at relationships and interaction), scale (both temporal and spatial), and multiple perspectives.

If, just for argument’s sake, we separate the world we inhabit into social systems and “natural” or ecological systems, and we assume that these exist as separate entities, we can imagine how human activities such as eating and manure disposal change the context in which we live, and how those ecological changes in turn change human societies. We change human social systems by the way we design cities, produce and distribute food, the way we handle manure, trade, travel, create transportation systems, build dams, and harvest trees. These changes in social systems in turn change the flows of energy, materials, and information (genetic, behavioral, cultural) through ecological systems. These changes in flows then create different outputs (changes in water flows, emerging diseases because of encroachment on wild areas, generating heat islands from paving areas or cutting down trees). Circling back around, these different outputs put pressure on social systems to adapt. Suddenly we are faced with pandemics of new diseases (SARS, for instance) or storm surges in major cities (such as tropical storm Sandy), for which our infrastructure is not prepared.

Related to this characterization of how social and ecological systems interact is the notion of emergence: when many variables interact, something entirely new may emerge. Or at least, if we look at the world in different ways, we may see something new. Think back to the exercise of looking through the microscope and the standing back that I introduced in the chapter on evolution. Single cells interact to create multi-cellular animals in an ecological context, but we don’t see the animal until we step away from the microscope. We don’t see a forest or a grassland until we step away from the tree or the blade of grass. Sometimes some genuinely new thing comes into being. Who would have predicted a boreal forest based on the first unicellular life forms? Who would even predict the flows and boundaries of such a forest based on looking at a couple of trees?³

The late James Kay, a world-renowned systems design engineer, ecologist, and physicist, explicitly teased apart how interacting changes in social systems and ecological systems were linked through flows of energy, materials, and information. By studying a wide range of situations, from urban parks and rural agriculture to industries and large-scale protected areas, and combining what we can visibly see with a deep understanding of the complex energy flows in ecosystems, he was able to extract some general principles. Social systems, when faced with an energy gradient across their boundaries (inputs of energy by fossil fuel, or embodied in people and animals) build material structures (armies, businesses, farms, skyscrapers) to use and dissipate that energy. The structures, built from the materials available and at hand, physically change the landscape in terms of energy, materials, and information (genetics, biological structures, learned behaviors, acquired knowledge). This changes the natural systems that formed the context and inputs for the social systems in the first place.

Suppose people wish to decrease the price of chicken and make it more available to people with low incomes; these are social goals, the result of changes in political and business organizations. Using massive inputs of fossil fuels, people accomplish this by completely restructuring the physical landscape of agriculture to accommodate the growing of grain crops to feed the chickens, as well as to provide consistent, climate-controlled housing for the birds. This changes the way rural communities are organized and how they relate to cities, and creates opportunities for bacteria to find new pathways into social systems. So, as long as the sun shall shine or we mine stored solar energy (fossil fuels), social-ecological systems are faced with energy gradients and are caught in endless feedbacks of re-structuring.

In the same way that a human body is something more than the sum of its chemical interactions, an urban society with certain resource demands creates something more than its constituent parts. The accumulations of manure, and the new diseases that we see are part of that new entity, and may not be controllable without changing some fundamental organizational structures in agriculture and land use. Seven billion people on Earth create a qualitatively different social and ecological dynamic than one billion.

We have talked about how human communities interact with, and change, the ecosystems in which they are embedded. This does not only happen locally. These changes happen at every scale (individuals, households, neighborhoods) and across scales (individual car use collectively changes the global atmosphere).

The kinds of resilience, integrity, and health that interest us when we pursue research into sustainable development can only be understood in terms of interactions across many geographic and organizational scales.

Depending on which research literature you read, such systems are variously called: complex adaptive systems; self-organizing, holarchic,⁴ open systems; or social-ecological systems. In general, the “complex adaptive” and “self-organizing” refer to the fact that healthy or resilient natural systems will, in the face of various external pressures, maintain their essential functions. Species may disappear and temperatures may rise, but as long as the remaining organisms can still organize themselves to build structures to deal with increased incoming energy, and can recycle essential elements such as phosphorus and nitrogen, they will survive.

What does that re-structuring and self-organizing look like over time?

It used to be said — based on limited observation of ecological changes — that all ecosystems move through succession from immature to mature states and somehow stay there. Now the situation does not appear quite so simple. The Resilience Alliance, a worldwide network of researchers investigating issues of linked social-ecological change, has studied sustainability and change in ecosystems at multiple scales. Their original conclusion, building on the groundbreaking work of Canadian ecologist C.S. “Buzz” Holling, was that every ecosystem went through four phases of development.

In phases 1 and 2, various species compete and cooperate to create structures in particular ecosystems. These phases are called exploitation and conservation; at some point, perhaps when the system is “over-connected” it becomes brittle, collapses, and goes through a process of reorganization (phases 3 and 4). Holling first called breakdown and renewal in ecosystems “creative destruction” but, apparently under attack from scientists for whom the creative and intelligent use of language is a foreign concept, later renamed the turning points to “release” and “reorganization.”

On a small scale, the creative destruction in this cycle was reflected in small forest fires, small patches of spruce budworm destruction, small outbreaks of disease. After the small fire or outbreak, plenty of genetic and nutritional material was available nearby for renewal.

When the local fires or outbreaks were suppressed, leaving lots of dead wood and disease-susceptible trees around, we scaled up the problem. The result was huge fires and disease outbreaks. The point is that if we remove some species from a natural system, or change the relationships in that system from how they have developed over time, we need to carry out the functions of the species we have removed. We need to relate differently to the ecosystem we have altered, to deliberately perform the ecological functions performed by the fires and outbreaks (removal and recycling of old, dead, or brittle materials, plants, and animals, re-seeding, fertilizing). Some functions are more difficult to replace than others. If we inadvertently destroy dung beetles, who will perform their functions? If we remove seed-dispersing bats or birds or pollinating insects from the equation, what happens to the options for renewal?

With great success, farmers have harnessed this process by planting new seeds, killing all the plants and animals they don’t like, harvesting the “mature” crop, destroying the remaining plant structure of the landscape (plowing), and, finally, renewing the fields with seeds of the plants (perhaps new, genetically modified ones) they want. These farming activities are based on anticipation that next year will be like last year. The farmers’ anticipation is, however, different from, say, a marine fish, whose life cycle assumes certain stable temperatures and food availability. The farmers change the present (e.g., plant more corn) in anticipation of both a stable climate and a higher price for corn. If all the farmers plant corn, they change the landscape, contribute to an unstable climate, and drive down the price of corn. I’ll come back to this later, because there is an upside to this as well.

Local events interact with larger-scale events across spatial and temporal scales, changing how life evolves on the planet. Large-scale changes — in climate, agricultural practices, or urban land development — alter the amount of exergy,⁵ and the kinds of information and materials (nutrients, elements, seeds, and animals) available for local renewal. We are then caught in a whole set of complex feedbacks. Genetic “innovations” and “revolutions” and “counter-revolutions” at a local level can radically change what happens at larger scales. These local changes might be related to, for instance, antibiotic use and the evolution and spread of resistant bacteria, or changes in livestock-rearing practices contributing to climate change and the global cycling of nitrogen, phosphorus, or water. If by changing some of the components we actually alter the relationships that provide the context within which species live and evolve, then species start to disappear. They become like refugees from “the former Yugoslavia”: their country disappears. The species literally have no job to go back to.

It used to be suggested that you could rebuild an ecosystem if you saved all the pieces. We’re no longer so sure that this can happen. Gene banks are interesting, but they’ll never get us “back” to where we were before, since what genes “do” is determined by the context in which they occur.

What is important to note for our consideration of excrement is that the reorganization and renewal of any social-ecological system, in the face of ongoing, incoming energy, depends on the materials and information that are available to it. When we see large piles of manure outside a feedlot or chicken barn, or large manure lagoons outside a pig farm, what we are seeing is a loss of information. We can only regain that information, and achieve some degree of resilience, if the manure is an integral part of the relationships among organisms in an ecologically diverse landscape.

Large-scale industrial agricultural enterprises and the big cities they serve may be efficient at processing energy, but they are brittle in the face of major change. They do not have the diverse internal resources or connections to use the information in adaptive, self-organizing ways. The information they might have used is all piled up in a dung heap.

There is no single way to think about all of these interacting changes, but there are a variety of useful possibilities.

The Resilience Alliance researchers have termed the multiple, multi-scalar growth, collapse, and change that we see around us “panarchy.” Sustainable development is seen, in panarchy terms, as a process of innovation and memory, revolt and stability. The innovation and revolt tend to occur locally, from the ground up. The memory and stability are encoded in long-term climatic and cultural patterns.

Philosopher Arthur Koestler talked about nature as being like the two-faced Roman god Janus. Each organism, person, family, or watershed is both a whole, with its own internal rules and feedbacks, and a part of something larger. Koestler called each of these whole-parts a holon, and called the overall structure a holarchy. In recognizing both the structural insights from Koestler and the dynamics of panarchy, Henry Regier, environmental scientist and former director of the Institute of Environmental Studies at the University of Toronto, introduced the term “holonocracy.” Holonocracy embodies a way of interpreting nested social and ecological changes and implies a new way to think about management and governance based on those observations. Democracy is generally interpreted as being “flat” — populations of people with equal standing before the law. In an autocracy, one person has unlimited power over everyone else. Often, the debate in politics is based on a binary view of the world: the individual versus the state.

Viewing politics and governance only as they relate to individuals and states is not helpful in solving the challenges of living in an overcrowded, unstable, interactive, extremely puzzling world. What I find more helpful is a view that sees micro-organisms as part of tiny micro-landscapes (in an intestine, for instance), which are part of larger communities (animals and plants on a landscape) and ecosystems (cycling nutrients), all the way to the biosphere and the universe. Similarly, the individuals within which the bacteria live can be seen as members of households, who are parts of communities that work together in larger geographic regions, all the way up to the globe. Each unit (bacteria, animal, turd) interacts with, and is indeed part of, larger units of nature, and is comprised of smaller ones, all the way down to the invisible bits that physicists look for.

Regier’s holonocracy, together with panarchy and Kay’s models, give us frameworks for how to think about and manage all this shit, not just to describe it. Tailoring options to fit local conditions creates problems for policymakers and managers, who want a “one-size-fits-all” solution. In natural systems, every solution to excrement recycling is very finely tuned to local conditions. Well-meaning environmental laws designed to control manure use in industrialized systems are a double-edged sword. They might work for big feedlots, but trying to force small farmers and local communities living under diverse conditions to adopt solutions and regulations suitable for large-scale industrial operations represents a kind of top-down dictatorship. This can put many smaller operators out of business and discourage neighborhood-based actions in cities. The expense of some systems only makes sense at large economies of scale; furthermore, this approach can suppress innovation to find more effective, less expensive, locally adapted solutions for dealing with manure. If we think in terms of a holonocracy, the purpose of national and global policy is to provide rules, support, capacity, information, money — to provide whatever is needed to help local communities and ecosystems to thrive — and to supply resources for renewal when local collapses occur.

How can we begin to assess the resilience of social-ecological systems? How can we “see” the movement of materials, information, and exergy? One way is to use, heuristically or metaphorically, observations on the relationships among plants, animals, and other organisms. Ecosystems are made up of (1) primary producers, which use sun and physical factors in the environment to make food; (2) consumers: animals (including ourselves), and bacteria that use, combine, and transform producers, food made by producers, and/or other consumers; and (3) decomposers: micro-organisms that break down dead organisms and organic waste. These three types of organisms are the physical manifestations of the dynamics of ecosystems; they perform the functions of cycling nitrogen, say, or water, even as they perform the functions of building structure and systemic resilience.

The life histories of parasites and insects and plants reveal a set of pathways by which the survival, growth, and adaptation of bacteria, insects, plants, and animals are linked across time and space. They reveal that, indeed, we are all that invisible shit made manifest, and that the natural order of life is based on shit.

In evolutionary terms, ecological systems “self-organized” and stayed resilient by reusing, repackaging, and recycling nutrients in forms that we would call waste, or shit, if we are talking specifically about animals. If we follow through on the general argument that more resilient systems are better at dissipating energy, then the more pathways for energy use a system can develop, the more it can keep on creatively (and thoughtlessly) organizing itself, and the more resilient it is. Can we mimic this diversity of pathways, and reclaim some measure of resilience, as we invent new kinds of living spaces and ways to feed ourselves?

I believe we can. If we understand the world, and our place in it, based on a more complex view of reality than we have been taught, if we go beyond normal science and politics to accommodate multiple perspectives, and multiple and complex systemic models, we can co-create a sort of global, open-ended narrative. Unlike the farmer who depends only on corn, or the city whose health is at the mercy of one or two treatment plants, a viable flush system, and a regional power grid, we want to create a situation where we have the capacity to anticipate a variety of futures.

If the world is a place for which we have no single description of a problem, and where the multiple perspectives held by microbiologists and anthropologists, shamans and epidemiologists, ecologists and economists, farmers and sex workers and musicians each have some validity, some truth, then how can we proceed? How do we accommodate multiple, jostling perspectives and maintain quality of information, and not just accept any flakey idea that comes along? How do we get all these diverse and often antagonistic people engaged in telling a collective, adaptive, diverse story?

Engagement by all these people in the process of generating knowledge and creating a working understanding of the world is not simply a way to facilitate political agendas, or promote new products, or gather people’s opinions. Citizen engagement and multiple perspectives are an essential part of any new way forward, out of the dung pile and into the fresh air. Everyone brings to the table different kinds of evidence in the same way that a personal narrative history, a clinical examination, an epidemiological study of varying populations at risk, and a laboratory test inform a clinical medical decision. Participatory-action research and its relatives are not merely ways to get people involved and to develop more effective solutions, as important as that is.

Public engagement is essential to do good science in a context where the facts are in dispute, values are contested, knowledge is uncertain, decisions are urgent, and decision stakes are high. Philosophers of science Silvio Funtowicz and Jerry Ravetz have called this post-normal science, because it is not about overthrowing or replacing the many paradigms of science, but of accommodating them. It is a democratic kind of science, open to different kinds of knowledge and differing interpretations of the facts.

Anything less than this leaves open too wide a possibility that we are all psychotic, believing that we can manage to fit the world into any one single vision. That we believe in final solutions to disease, or poverty, or economic disparity. Anything less than this new science leads to the tyranny of public health warring with the tyranny of free trade economics warring with the tyranny of environmental policy.

But what is the point of this new science? Democratization of knowledge? Yes. Better science? Yes. But to what end? For the obsessively curious, this may be enough. But those of us who maintain illusions of changing the world, who want to move from knowledge generation to policy and action, we need a goal, something to inspire us and give us focus.

Resilience has been offered up as a goal by many ecologists. I have no quarrel with that. Another useful way to articulate the goal of this new science — one that can accommodate, in particular, the challenge of excrement and get the attention of people who otherwise don’t care about “the environment” — is health. Not just any health: One Health.

Rene Dubos, one of the great public scientists of the twentieth century, described health as a mirage, since it was forever shimmering somewhere on the horizon but never attained. But health is attained every day and reinvented and rejuvenated in every culture. It is not a mirage; sensitive as it is to what people eat, who their friends are, the amount of sunshine they are exposed to, the weather in general, the quality of water, health is a renewable way of being. We all want to be in a state “of complete physical, mental, and social well-being and not merely the absence of disease or infirmity,” which is how the World Health Organization (WHO) defined health in its 1948 constitution. Some of my colleagues have suggested that this sounds like an orgasm, something to enjoy periodically, but not a sustainable state.

Even with that caveat — some would suggest especially with that caveat — most of us would agree with the proposition that health is a good thing for all species, including people, and the planet we share. This is what the World Health Organization, the World Organization for Animal Health, the World Bank, the United Nations, and multiple government and nongovernmental agencies around the world call One Health.

One might well ask, when we speak of One Health: Whose health? North Americans? Africans? Asians? Rich people? Poor people? Our children’s children? Most importantly, individual health or population health or community health? Because it is possible to pour millions of dollars into saving and vaccinating babies, and, without equal attention to education, meaningful work, food security, we may make things worse — much, much worse — for those children when they grow up. Can we pull back from the catastrophic brink that an already overcrowded planet has pushed us to?

If we pour millions into keeping older people alive, what does this mean for the draw on resources needed for those children to having meaningful, fulfilled lives? Are we not then promoting global poverty, youth unemployment, and its natural, well-demonstrated consequence, war? If we put flush toilets and running water into slums so people can wash and drink, while drawing down already precarious water tables, what does the future hold for them? Or if we advise people in the Amazon to eat fruit-eating fish, rather than carnivorous fish, to avoid mercury poisoning, will we remove a source of dispersal for fruits trees, and what will be the consequences of that? If we focus only on food production and manure management as global goals, without paying attention to how we achieve them, will we not make things worse? Haven’t we already done so?

And if we ask these questions, we have to deal with tragedy, loss, and suffering. We have to deal with all the cultural rituals, music, poetry, religion, with which we manage our grief. Because, in the long run, health for all means grief for many.

Yet health is a sufficiently robust idea that it somehow continues to engage us, and keeps us talking, even as we struggle with the details. And in talking together, we are already creating the social bonds that foster health. One Health provides a space for us to argue about who we are, who we want to become, and about all that shit out there that we are unsure how to “manage.”

Health, in a global sense, expressed somewhat differently in each culture, remains an overarching goal, universally (if imperfectly) understood and desired. Yet why is it that this ideal of health seems to keep slipping away from us? Are we thrown back to the details of who and where? Of manure problems versus regional famine? Of babies against old people? Of climate instability versus meaningful work?

Conventional technical and scientific wisdom might have us believe that how we achieve goals is irrelevant. All that matters is a diagnosis and a technical treatment. And yet we know, by and large, that this doesn’t work.

We can tell people not to smoke, to eat better, to exercise, to vaccinate their dogs, not to let their dogs or chickens run in the street, not to dump their manure where they please, and on and on, yet, in the full knowledge of what they are doing, they resist changing their behavior. This is not because they are stupid. This is because people are working with multiple demands on their time and attention, and the world does not function like a factory or a clock, with linear cause-effect chains. The world is a mess of interactions, and every ecosystem and social-ecological system we can imagine about the world is a simplification, a simplification from which we learn, but which nevertheless is incomplete.

The only defensible way to act is by engaging with others, sharing information, changing our minds, being humble in the face of an amazing universe.

How we act is as important as the goals we set. With One Health as a goal, complexity as a theoretical base, and post-normal science as a guiding principle for linking science with action, we can move forward with telling the story of our lives on this amazing and sometimes infuriatingly contrary planet. This way of framing and addressing wicked health issues, often referred to as ecohealth (short for ecosystem approaches to health), has led us from a manure pile next to the barn to linked social-ecological systems to a new way of doing science. Now is the time, I think, for us to think about solutions.

1 Details of the general theory and practice set out in this chapter and the next are addressed in much greater detail in The Ecosystem Approach: Complexity, Uncertainty, and Managing for Sustainability (New York: Columbia University Press, 2008); Ecosystem Sustainability and Health: A Practical Approach (Cambridge: Cambridge University Press, 2004), and Ecohealth: A Primer (Victoria: Veterinarians without Borders/Vétérinaires sans Frontières – Canada, 2011. Available as a free download at https://www.vetswithoutborders.ca/get-involved/resources).

2 There is no good word to describe the kind of limited scientific inquiry I am talking about. Reductionist, linear, and industrial have all been used. This kind of science is often associated with laboratory experiments where “all other things” are assumed equal, or under control. In this view, science is comprised of multiple disciplines, each with different rules of evidence, and the “whole” is, in some simplistic way, considered to be the sum of the parts. I suppose I am talking about what Thomas Kuhn called “normal science,” and I shall use that as a kind of shorthand. I am not dismissive of that kind of science. It is excellent for answering some kinds of questions (measuring drug efficacy in hospitals, assessing chemical hazards) but is weak at addressing the questions I am trying to get at in this book.

3 A common example given for this is the birth of the internet, which was not predictable based simply on the known pieces of communications technology and human behavior.

4 James Kay called these SOHOs. I’ll talk more about holarchy and holarchic later.

5 Exergy is a term some systems engineers use for “useful energy.” Energy is not created or destroyed, but some forms of energy (meat) seem to be more useful to us than others (shit). Exergy thus considers both the inherent energy (what a physicist might measure) and the context (how we wish to use that energy). Actually, shit still has a lot of energy, and if we change how we use it (the context), we can use that energy, instead of throwing it away.