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Out of Control

Yet there was still an art to it. As Packard knotted the web, he noticed that it mattered what order he added the pieces in. And he learned that other ecologists had discovered the same thing. A colleague of Leopold had found that he got closer to a more authentic prairie by planting prairie seed in a weedy field, rather than in a newly plowed field, as Leopold had first done. Leopold had been concerned that the aggressive weeds would strangle the wildflowers, but a weedy field is far more like a prairie than a plowed field. Some weeds in an old weedy lot are latecomers, and a few of these latecomers are prairie members; their early presence in the conversion quickens the assembly of the prairie system. But the weeds that immediately sprout in a plowed, naked field are very aggressive, and the beneficial late-arriving weeds come into the mix too late. It's like having the concrete reinforcement bars arrive after you've poured the cement foundation for your house. Succession is important.

Stuart Pimm, an ecologist at the University of Tennessee, compares succession paths -- such as the classic series of fire, weed, pine, broadleaf trees -- to well-rehearsed assembly sequences that "the players have played many times. They know, in an evolutionary sense, what the sequence is." Evolution not only evolves the functioning community, but it also finely tunes the assembly process of the gathering until the community practically falls together. Restoring an ecosystem community is coming at it from the wrong side. "When we try to restore a prairie or wetland, we are trying to assemble an ecosystem along a path that the community has no practice in," says Pimm. We are starting with an old farm, while nature may have started with a glacial moraine ten thousand years ago. Pimm began asking himself: Can we assemble a stable ecosystem by taking in the parts at random? Because at random was exactly how humans were trying to restore ecosystems.

In a laboratory at the University of Tennessee, ecologists Pimm and Jim Drake had been assembling ingredients of microecosystems in different random orders to chart the importance of sequence. Their tiny worlds were microcosms. They started with 15 to 40 different pure strains of algae and microscopic animals, and added these one at a time in various combinations and sequences to a large flask. After 10 to 15 days, if all went well, the aquatic mixture formed a stable, self-reproducing slime ecology -- a distinctive mix of species surviving off of each other. In addition Drake set up artificial ecologies in aquaria and in running water for artificial stream ecologies. After mixing them, they let them run until they were stable. "You look at these communities and you don't need to be a genius to see that they are different," Pimm remarks. "Some are green, some brown, some white. But the interesting thing is that there is no way to tell in advance which way a particular combination of species will go. Like most complex systems, you have to set them up and run them to find out."

It was also not clear at the start whether finding a stable system would be easy. A randomly made ecosystem was likely, Pimm thought, "to just wander around forever, going from one state to the next and back again without ever coming to a persistent state." But the artificial ecosystems didn't wander. Instead, much to their surprise, Pimm found "all sorts of wonderful wrinkles. For one, these random ecosystems have absolutely no problem in stabilizing. Their most common feature is that they always come to a persistent state, and typically it's one state per system."

It was very easy to arrive at a stable ecosystem, if you didn't care what system you arrived at. This was surprising. Pimm said, "We know from chaos theory that many deterministic systems are exquisitely sensitive to initial conditions -- one small difference will send it off into chaos. This stability is the opposite of that. You start out in complete randomness, and you see these things assemble towards something that is a lot more structured than you had any reason to believe could be there. This is anti-chaos."

To complement their studies in vitro, Pimm also set up experiments "in silico"-simplified ecological models in a computer. He created artificial "species" of code that required the presence of certain other species to survive, and also gave them a pecking order so that species B might drive out species A if and when the population of B reached a certain density. (Pimm's models of random ecologies bear some resemblance to Stuart Kauffman's models of random genetic networks; see chapter 20). Each species was loosely interconnected to the others in a kind of vast distributed network. Running thousands of random combinations of the same list of species, Pimm mapped how often the resulting system would stabilize so that minor perturbations, such as introductions or removals of a few species, would not destabilize the collective mix. His results mirrored the results from his bottled living microworlds.

In Pimm's words, the computer models showed that "with just 10 to 20 components in the mix, the number of peaks [or stabilities] may be in the tens, twenties or hundreds. And if you play the tape of life again, you get to a different peak." In other words, after dropping in the same inventory of species, the mess headed toward a dozen final arrangements, but changing the entry sequence of even one of the species was enough to divert the system from one of the end-points to another. The system was sensitive to initial conditions, but it was usually attracted to order.

Pimm saw Packard's work in restoring the Illinois prairie/savanna as validating his findings: "When Packard first tried to assemble the community, it didn't work in the sense that he couldn't get the species he wanted to stick and he had a lot of trouble taking out things he didn't want. But once he introduced the oddball, though proper, species it was close enough to the persistent state that it easily moved there and will probably stay there."

Pimm and Drake discovered a principle that is a great lesson to anyone concerned about the environment, and anyone interested in building complex systems. "To make a wetland you can't just flood an area and hope for the best," Pimm told me. "You are dealing with systems that have assembled over hundreds of thousand, or millions of years. Nor is compiling a list of what's there in terms of diversity enough. You also have to have the assembly instructions."