November 25, 2017

Ecologists in a distorting mirror

Book Review: Systems Ecology by H. H. Shugart and R. V. O’Neill. Dowden, Hutchinson & Ross Inc. Pennsylvania.

Published in The Ecologist Vol. 10 Nos. 1/2, January/February 1980.

This is a collection of papers that have already appeared in various specialised journals such as Simulation, The Journal of Dynamic Systems, Measurement and Control, Ecology and also Nature and Science. If a technical appreciation of these papers is required then I am clearly the wrong reviewer as I am not at all convinced of the basic assumptions underlying the methodology these papers make use of and advocate.

The first thing that strikes one is the gulf that separates professional mathematical ecologists (with a small e) from Ecologists (with a big E) such as myself who regard ecology as an approach – one that basically involves looking at problems in their total temporal and spatial context, rather than in isolation from each other as is currently the practice among most modern scientists.

If one applies this approach then it becomes apparent that most of the problems that confront us today are due to the increasingly intolerable impact of our industrial activities on the ecosystems that make up the biosphere. Our first priority must be to reduce this impact and, this means more than anything else, moving away from expensive high technology to what is increasingly called alternative technology; better still to the full use of the far more sophisticated mechanisms of nature – such as those that enable forests to absorb C02, generate oxygen and control the run-off to rivers.

The authors of this book see things very differently. They have in common with Norman Bell and Herman Kahn, a naïve, quasi-religious faith in the virtues of high technology which is irreconcilable with ecological understanding of the world we live in. Consider the following passage from G. M. Van Dyne’s paper, “Ecosystems, Systems Ecology and Systems Ecologists”:

“The role of computers in tomorrow’s technology will have larger and faster memories, remote consoles, and time-sharing systems. Some may accept hand-written notes and drawings, respond to human voices, and translate written words from one language into spoken words in another. There will be vast networks of data stations and information banks, with information transmitted by laser channels over a global network.”

To me this statement sounds like a spoof on a technomaniac’s recitation of his credo. What can all this gadgetry do for one? Very little I am sure, as David Reichle and Stanley Auerback’s paper “The Analysis of Ecosystems” makes fairly clear. They explain how essential all this gadgetry is, for examining the changing land-use patterns in eastern Tennessee:

“A simulation model was developed based upon known plant succession for the region and land use trends derived from aerial photographs spanning 25 years. Predictions were made of the rates of change of various landscape categories for a five-county region. The rates of change for different vegetation types are related to the rates of plant succession and can be evaluated using empirical data from the field. The annual loss of non-forested land for the five-county area was 5.28 per year, of which 2.39 per year represented an increase in forested land (primarily due to the influence of a paper mill on the establishment of pine plantations) and 2.85 per year was irreversibly lost to reservoirs (TVA dams in the Valley) and urban development.”

In other words they are telling us that a vast academic study stretching out over 25 years and making use of incredibly complicated and expensive computers is required to tell you that the implantation of a paper mill is likely to lead to the development of tree plantations to provide it with its raw material and that the building of reservoirs will lead to the loss of agricultural land – a local shepherd could have given you the same information at the cost of a pint of beer in the local pub.

Another example is derived from the same paper. Reichle and Auerback tell us that:

“The conflict between demands for increased power production and improved environmental quality can be approached by integrating economic and ecological theory in a functional systems analysis. Consider the current problem of ‘blackouts’ or ‘brownouts’ in major cities as evaluated through a socio-economic model by Chapman and 0 ‘Neill (1970). Intersection of the market supply and demand functions defines the market equilibrium, Xme, with price Pme. Environmental impact of power generation, as perceived by society, causes a new (social) equilibrium, Xse, defined by the intersection of the marginal social cost and marginal social value functions. Differences between equlibria create conflict between construction plans of power companies and conservation groups. At the total power production from plants actually built, Xas, the utility incurs market costs, Cma. The regulatory agency requires the utility to set its market price, Pma, at or near Cma. With price, Pma, public consumption demands quantity, Xad which is substantially in excess of the amount, Xas, that can be supplied. This study illustrates how the energy production/utilisation system is coupled in such a way that demand can exceed supply and cause brownouts.”

This example is just as laughable, as the other. What on earth do we learn by being told that “blackouts” or “brownouts” will occur at “the intersection of the marginal social cost and marginal social value functions”? Does it enable us to predict how much pollution has to be caused by the power industry before environmental groups start complaining or what pressure they are likely to apply to prevent any further pollution? It tells us nothing at all, it is just a pretentious and very clumsy way of saying nothing.

Having read this book I have to be persuaded that there is a single lesson of any real importance about the behaviour of natural systems which can be derived from a computer study that a man of average intelligence will not be able to work out for himself. I am yet to be persuaded among other things, that quantification itself is of any usefulness for understanding the behaviour of natural systems. The editors inform us that mathematical modelling has been of particular use in the field of demography. This is no recommendation. Demography is a miserable subject. I have never heard of any demographer making an accurate forecast.

In general, to determine the usefulness of quantifying the factors mathematical systems ecologists take into account, we must first determine what they are trying to achieve. According to Reichle and Auerbach,

“the goal of ecosystem analysis is to develop a quantitative ecosystem science which may provide new theoretical insights into the organisation and function of natural Systems at their most complex level.”

But what makes the authors think that it is by measuring things that these new theoretical insights can be obtained? The important factors involved in determining the behaviour of natural systems, especially at a high level of organisation, are usually non-quantifiable.

Take the case of demography. What are the factors influencing population growth? It is certainly not the number of birth control devices that are distributed within a population, as most people in the population control business still seem to think. Otherwise how do we explain that the population of France was stationary during the inter-war years when no birth control devices were available on the market? Nor is it protein availability, certainly if taken by itself, for hunter gatherers lived off perhaps 30 percent of available food resources, so we are told and their numbers remained constant for hundreds of thousands of years.

I think that it can be shown that the, really operative factors are of a psychological nature. In France during the inter-war years, people had a sense of responsibility and did not have children until they felt they could look after them properly. In North and Central Italy, people still have such a sense of responsibility, though not in the South where they breed like rabbits. If population growth has stopped in the West today it is probably also for psychological reasons. Attitudes have changed. Perhaps people see the future as being too bleak, which may be the reason, too, why population growth fell during the depression in the 1930s.

Demography is not an exception in this regard. I think it can be shown that in almost every field of behaviour, the important factors involved are non-quantifiable. To insist, as our scientists do today, that only quantified factors can be taken into account, means that their attention has shied from the study of important (non quantifiable factors) to that of trivial (quantifiable ones), which is undoubtedly one of the reasons why scientists are not coming out with any of the answers to the problems that confront our society today.

My feeling is that if this book is a fair sample of mathematical systems ecology, then this is a largely academic exercise of little interest to serious people who are trying to understand what is happening to the world around us with a view to offering serious workable solutions to such problems.


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