James Lovelock on the Vanishing Face of Gaia

    Excerpt from The Vanishing Face of Gaia: A Final Warning, by James Lovelock (Penguin Books, 2010). Reprinted with permission from the author.

    Chapter 7: Perceptions of Gaia

    Science is broadly divided between the rational Cartesian thinking of Earth and life scientists and the holistic thinking of physiologists, engineers and physicists. The holistic scientists speak in mathematical languages and are all too often incomprehensible to the rationalists. Rational scientists dislike insights; they much prefer step-by-step explanations based on reliable and orderly data. Insight they see as the child of intuition, something irrational drawn from a mess of apparently conflicting data. Dislike it they may, but the large steps in science come as often from insight as from rational analysis and synthesis. This is especially true of quantum physics and of the science of living things; indeed it may never be possible to define life or quantum entanglement in rational scientific terms. Charles Darwin recognized by insight that the evolution of all living organisms is governed by natural selection, or as Jacques Monod put it, through the operation of chance and necessity, but it was not until fifty or more years later, and after a lifetime of research and evidence-gathering by Darwin himself, and later by Mendel, that the full scientific significance of evolution was established by such able men as Fisher, Haldane, and Ernst Mayr, and more recently John Maynard Smith, Robert May, and Bill Hamilton. Even then it was only one hundred years after Darwin that his apostles E. O. Wilson and Richard Dawkins made it publicly comprehensible. We now have the insight of Gaia that Darwinian evolution is constrained by feedback from the material environment. Thus simply by breathing we add carbon dioxide to the air, which has consequences for everything alive on the Earth, including us, and for the evolution of the whole great system. Gaia is a holistic concept and therefore unpalatable to rational Earth and life scientists. Physicists and physiologists, used to handling the literally incomprehensible, take Gaia and other holistic concepts as useful and are glad to work with them. But there is still a long way to go before Gaia is understood as well as evolution by natural selection. I think it’s significant that William Hamilton, arguably the greatest biologist of the twentieth century, called the concept of Gaia Copernican, but he added that it would take another Newton to explain how Gaian self-regulation took place through Darwinian natural selection.

    My reason for persisting in calling the Earth Gaia and saying it is alive is not a personal foible; it is because I see this as an essential step in the process of public, as well as scientific, understanding. Until we all feel intuitively that the Earth is a living system, and know that we are a part of it, we will fail to react automatically for its and ultimately our own protection. It was not until 2004 that a few of us around the world, including Tim Flannery and Al Gore, came to the insight that climate change was more than an academic scientific project but instead a menacing reality, and one that threatened all of us. Before 2004 the debate about Gaia concerned only me and a relatively small number of scientists, but now a proper understanding of the Earth as a living planet is a matter of life or death for billions of people, and extinction for a whole range of species. Unless we accept the Earth as alive, with us as a part of it, we may not know what to do or where to go as the ocean rises on a hot dry world. For this purpose the name Gaia is far more suitable for a vast live entity than some dull acronym based on rational scientific terms. In ancient Greece, Gaia was the goddess of the Earth. To many Greeks, she was the most revered goddess of all, and interestingly the only god or goddess that was never the subject of scandal.

    May I remind you why I call the Earth Gaia? It came about in the 1960s when the author William Golding, who subsequently won the Nobel and many other prizes, was a near neighbor and friend. We both lived in the village of Bowerchalke, twelve miles southwest of Salisbury in southern England. We would often talk on scientific topics on walks around the village or in the village pub, the Bell Inn. In 1968 or 1969, during a walk, I tried out my hypothesis on him; he was receptive because, unlike most literary figures, he had taken physics while at Oxford as an undergraduate and fully understood the science of my argument. He grew enthusiastic and said, “If you are intending to come out with a large idea like that, I suggest that you give it a proper name: I propose ‘Gaia.’” I was pleased with his suggestion—it was a word, not an acronym, and even then I saw the Earth as in certain ways alive, at least to the extent that it appeared to regulate its own climate and chemistry. Few scientists are familiar with the classics, and are unaware that Gaia is sometimes given the alternate name “Ge.” Ge, of course, is the prefix of the sciences of geology, geophysics and geochemistry. To Golding, Gaia, the goddess who brought order out of chaos, was the appropriate title for a hypothesis about an Earth system that regulated its climate and chemistry so as to sustain habitability.

    My first book, Gaia: A New Look at Life on Earth, was written in the 1970s, mostly in Ireland. Perhaps because of the deeply religious sensibility of that land, I wrote: “There is no set of rules or prescription for living with Gaia, there are only consequences.” This was an insight and not a logically drawn scientific inference, but nothing has happened in the thirty years since to make me change my mind. Our understanding of the Earth has been hampered by the rapidity and success of model-making in computers. I am not for a moment suggesting that computer model-making is not a valuable and enjoyable activity; indeed much of modern science would not have happened without it. The difficulty arises because it is as easy to make computer models of the rational science of the twentieth century, as it is to make holistic models like the simple Gaia model known as Daisyworld. Once a large computer model is made and produces a believable result—especially if, when run backward, it successfully predicts the climate of the previous decades—then its forecasts of the future tend to be accepted as true. This is the state of many of the major climate models now in use by the IPCC. Gaia theory is a holistic, whole-system theory, and as such cannot be modeled using the concepts of the Earth or life sciences separately. Almost all science other than upmarket physics, physiology, and engineering is reductionist; in other words, it is about taking something to bits to reveal its ultimately irreducible parts, such as atoms or DNA. Holistic system science is concerned with intact working systems such as the Earth, living organisms, and self-regulating artifacts made by engineers. Apart from these dynamic systems, holistic science is still emerging and not yet commonly used in practice.

    Computers were first used in science by physicists to help them with difficult equations and with the mindbreaking complexities of the newly emerging concepts of quantum theory. It was not long before engineers with just as hard but more down-to-earth problems used them to improve their inventions, and later they built models that displayed a three-dimensional image of their widgets on the computer screen, images that could be rotated and poked at on the screen almost as if they were real. Engineers are practical people and I doubt if any of their models, no matter how real they appeared, went into mass production without the trial and test of a solid prototype. Other scientists began to compose models and use them to refine their ideas and experiments.

    In the 1960s and ’70s computers were hardly more powerful than a pocket calculator, and their program languages were peculiar. One such form of mathematical logic rejoiced in the name “reverse polish,” and not surprisingly nonmathematical scientists avoided it. By the 1980s fairly powerful computers were mass produced and easy to use. Just as the average driver has no idea of the working of a modern car, so scientists using the computer on their desk have no idea of its detailed working but confidently drive it to solve their problems. Earth and life scientists used computers to model the cycles of the chemical elements or the evolution of populations. Computer models are so helpful that before long many biologists and geologists put their field equipment in store and began a new life working with their models pretending that they were the real world. This Pygmalion fate—falling in love with the model—is all too easy, as generations of the young and old playing their computer games have found. Gradually the world of science has evolved to the dangerous point where model-building has precedence over observation and measurement, especially in Earth and life sciences. In certain ways modeling by scientists has become a threat to the foundation on which science has stood: the acceptance that nature is always the final arbiter and that a hypothesis must always be tested by experiment and observation in the real world.

    The slowness to accept Gaia theory was also due, I think, to the longevity of the ideas of genius. Just as the elegance of Newtonian physics delayed the emergence of modern physics, so did a rigid interpretation of Darwinism delay the acceptance of Gaia. We have a saying in science: “The eminence of a scientist is measured by the length of time he holds up progress.” The overarching genius of Descartes, the father of reductionism, still hampers the emergence of a holistic Earth science in which Earth and life science form a single discipline. His insistence on the separation of mind and body persisted as an influence so strongly that only in the last few years has the notion of “plasticity” become respectable: the concept that thought can change the physical structure of the brain and vice versa.

    Physicists and chemists make models but are usually aware of their limitations and almost always ask for experimental verification. Unfortunately Earth and life scientists can only rarely experiment directly with the Earth and are forced to be less pure. Too often the programs that define a model are composed by professional computer scientists or are even commercial modeling applications. The ideas included in the models may be those of the scientists, but the models may be mathematically incapable of handling them. It is as if we expected a car built to travel on roads would do as well across farmers’ fields and hedges. Ideally scientists should be personally engaged in the writing of their software, for in this way the model-maker has the chance to interact with the model and maybe even understand it.

    Trust in the validity of models made in isolation by Earth and life scientists had a malign effect on their understanding of the Earth and on the acceptance of Gaia theory. This was because life scientists failed to include a dynamically responsive environment and Earth scientists failed to include organisms that evolved and responded dynamically to environmental change. There was a fundamental and less excusable reason for their reluctance to engage in transdisciplinary modeling. The mathematics of dynamic self-regulating systems frequently involves differential equations that are difficult or impossible to solve by traditional methods. It is too easy to slip into the practice of making what are called “linearizing approximations,” and then forget their presence as the model evolves.

    Scientists of these separated disciplines should have realized that they were on the wrong track when quite independently the geophysicist Edward Lorenz, in 1961, and the neo-Darwinist biologist Robert May, in 1973, made the remarkable discovery that deterministic chaos was an inherent part of the computer models they researched. Deterministic chaos is not an oxymoron, however much it may seem like one. Up until Lorenz and May started using computers to solve systems rich in difficult equations almost all science clung to the comforting idea put forward in 1814 by the French mathematician Pierre-Simon Laplace that the universe was deterministic and if the precise location and momentum of every particle in the universe were known, then by using Newton’s laws we could reveal the entire course of cosmic events, past, present, and future. The first indication that this was too good to be true came in 1890 when Henri Poincaré studied the interaction of three bodies held together by gravity while orbiting in space; he found that the behavior of the system was wholly unpredictable. This was a serious flaw in the concept of determinism, but it was not until 1961 that Lorenz used an early computer to demonstrate the chaotic behavior of weather and found it to be wholly unpredictable beyond about a week. He was the originator of the “butterfly effect”—the idea that the small eddy made by the flapping of a butterfly’s wings could initiate much later a hurricane; he showed that this was because weather systems are highly sensitive to the initial conditions of their origin. May found that computer models of population growth showed similar chaotic behavior, especially in biological systems containing more than two species; these discoveries stirred great interest among mathematicians and scientists in the nature of deterministic chaos. Practical applications in communications and to new art forms have emerged, for example those stunning illustrations of fractal mathematics such as the Mandelbrot set. It was so human and apparently understandable that neither of these eminent scientists made much of the fact that the appearance of chaos suggested that something might be wrong with their hypotheses about the world. Lorenz and May were both looking at the Earth system from within separated scientific disciplines that took cause-and-effect determinism for granted. Yet if instead we look at weather and population growth as a single tightly coupled system we find it is wholly free of deterministic chaos. More than this, the combined model is resilient to perturbation and makes credible predictions. This is why I persist with my pleas to IPCC scientists to include in their models the Earth’s ecosystems in a similarly tightly coupled, responsive way.

    In no way do I imply that either Lorenz or May had blundered into chaos. They were the best of scientists and came upon chaos serendipitously; they had the wisdom to see it as a truly great discovery in itself and one that has enlarged both art and science.

    Excerpted from The Vanishing Face of Gaia by James Lovelock. Copyright © James Lovelock, 2010. All rights reserved.

    James Lovelock is undoubtedly one of the most outstanding and influential scientist-thinkers of our time, inventive, unorthodox, ingenious and a latter day Darwin. His establishment-science career reads like an honour role, and is reflected by his knighthood in 2002. Lovelock’s many inventions include the electron capture detector (ecd), which has been of major significance in increasing our knowledge of the environment. The ecd was also instrumental in the discovery of global pollution by fluoro-carbons, critical to both global warming and the hole in the ozone layer.

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