"Any idiot can respond to a crisis. The things that really wear you down are the everyday details of life." ---Attributed to Anton Chekov by the New York Times Crossword Puzzle.

I got up this morning and wandered to the bathroom, and within a few minutes the wastes my body had accumulated during the night were being transported away through a network of pipes to a sewage purification plant where they would be rendered harmless. Proceeding to the kitchen, I opened the refrigerator and found that I would not have to go out and milk my own cow in order to eat cereal for breakfast; someone else had fed, tended and milked a cow for me. The milk was delivered by someone to a place where my wife could buy it, and it did not spoil because somewhere there is a generating plant where fuel is brought in and burned to create electricity, and someone has strung wires from the plant to my house to make my refrigerator keep the milk cold. The temperature outside was below 40, but I was comfortable; somewhere someone dug a well to capture natural gas, and someone else made a pipeline to bring the gas to my furnace. I turned on the faucet and water came out; someone thoughtfully built a reservoir, purified the water for me, and piped it into town. I could go on, but you get the picture. What I have just described is a small fraction of what is popularly called "infrastructure," or, in more analytic terms, a system. Although we take systems for granted unless something goes wrong with one of their components, the fact is that we are completely dependent on them.

Economists, sociologists and political scientists have known that we live in a system for a very long time, but it was not known until about 70 years ago that systems are also the pattern of organization in nature. The term "ecosystem" was coined by a British biologist named Tansley in 1934, but he was ahead of his time; most biologists in those days were concerned more with describing the environment than analyzing it. For analyzing things, a different kind of thinking was required.

In terms of thinking, physicists were far ahead of biologists. Sometime in my first year of teaching I heard a discussion in which someone asked the Physics professor, John Richards, "What, at the most basic level, do scientists do?" John thought about it for a millisecond or so, and replied, "We make models." He went on to explain that the real world is too complicated to understand, so scientists have to make up simplified versions called models, which can be tested by various experiments to see if they behave the same as the real world does. A model can be a mechanical device like the gears that turn a projector in a planetarium to show how the planets move around the sun, or it can be an abstract idea like Einstein's mathematical equations. It was a curious bit of serendipity that I heard that conversation, for by that time ecologists were just beginning to think about making models of the ecosystem and using techniques we now call systems analysis to study them.

About the time I was taking my first ecology course in college, two Australian ecologists proposed a model in which the ecosystem was divided into four components: Weather, Food, Other Organisms, and, in their precise British diction, a "Place in which to Live." These components were visualized as four boxes in a diagram, and in a fifth box, between the other four, represented the population of animals being studied. Every time you found a relationship between the animals and one of the four boxes, you drew a line to connect the boxes. Then you tried to construct an equation that would show the effect of the relationship, i.e., whether it made the animal's population increase or decrease. It quickly turned out that you could make wonderfully complicated diagrams, but it was difficult to find equations that realistically described what was going on. Worse yet, when you did find equations, you had to solve them all at once because the influence of each environmental factor affected all the others.

As a simple example, in the 1980's pheasants were common in the fields around Emmitsburg, but one year they died out. That year there was a cold, wet spell during the nesting season, and many hatchlings died… draw a line from "weather" to the pheasant's box. Then there was a drought that summer, which resulted in a poor crop of berries and seeds… draw a line from the Weather box to the Food box, and another from Food to pheasants. The following winter, there was heavy snow which flattened the brier patches where the pheasants hid… a line from Weather to Place to Live, thence to pheasants. Poorly nourished and with nowhere to hide, more pheasants were killed by predators… hunters, foxes, owls, hawks, dogs…several lines from Other Organisms. And of course pheasants have parasites… lice, worms, etc., which normally they live with, but which may kill them when they are under stress… more lines from Other Organisms. So why did the pheasants disappear? Was it overhunting, predation, starvation, freezing, poor nesting success, disease… or something we haven't thought of yet? …or all of the above?

Making a diagram to model the pheasants in their ecosystem may give us a feeling of satisfaction, but it really doesn't give us an unequivocal answer to why the pheasants disappeared. In the 1950's when this model of the ecosystem was proposed, trying to create mathematical equations for each of the lines in the diagram only added to the problem; it was not possible to solve so many simultaneous equations by hand, and computers were not available. Today, we have better equations, but even a simple model can tie up the most powerful supercomputers for weeks and still not answer the question. Of course if it is just pheasants in Emmitsburg, it doesn't really matter in the great scheme of things; but similar models are used by people trying to understand traffic patterns around major cities, global warming, pollution, or the spread of AIDS. All of the major problems facing us are studied by applying systems analysis to computerized models; and all of them present intractable frustrations.

Although analyzing systems by means of models has not yet enabled scientists to solve any major problems, thinking in terms of models has nevertheless proved to be immensely valuable: it has made us realize how complicated the world is. Understanding that this complexity exists has two benefits. First, it makes us realize how vulnerable are the systems in which we live, whether they are ecosystems or socio-economic systems. We have learned that the more complex a system is, the more effort and resources must be spent on maintaining it. When every part of a system is connected to every other part, breaking just one line in the model disrupts the entire structure. This is why terrorism is so much more effective in highly developed societies than in underdeveloped ones. It is also why ecosystems are so vulnerable to pollution and over-exploitation.

The second benefit of being aware of complexity is that it warns us of the danger of trying to apply simplistic solutions to problems, be they ecological, economic or political. We see repeatedly that impulsively attacking one symptom of a problem without regard for all the other aspects of the system almost always makes things worse. As our world becomes more complex each day, and thereby more vulnerable, it is imperative that we have leaders who understand this. We must get it right; there will not be many more chances.