Environmental Sciences Research Paper

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The term ‘environmental sciences’ groups a number of disciplines which, in academia, are not usually found together. Ecology is a biological science, meteorology a physical science, and geology and physical geography also have their separate departments. Urban and regional planning is a social science. Yet all these sciences have important commonalties.

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First, they have shared historical roots. All entered the modern phase of their development around 1800. The term ‘Humboldtian sciences’ has been given to sciences which seek, as all of these fields do, to integrate large numbers of facts and measurements in a holistic image of their subject matter. There is a strong link with Romanticism, which, in the sciences, aimed at conceiving large wholes and finding their underlying patterns of organization. Yet, during a century or more, the various Humboldtian sciences increasingly developed within their own disciplinary boundaries.

However, from 1960 onward, the environmental sciences have again moved closer toward each other. Societal pressure played a large part therein, and the very word ‘environmental’ developed its momentum in the public realm before it entered scientific discourse to the extent that it has now (Jamison et al. 1990). Ecology was first science to receive its status as ‘the’ environmental science, not long after the publication of Rachel Carson’s Silent Spring in 1962 and more visibly after Earth Day in 1970. Governmental science policy in many western countries has been willing to recognize ecology’s centrality.

Meteorology much later than ecology rose to the status of an encompassing environmental science. It acquired this status around 1985. The ‘greenhouse effect’ occasioned primarily by human societies’ burning of fossil fuel, and the resulting ‘global warming,’ have inspired governmental policies on a number of levels. These policies in turn have exercised profound impacts on priorities in science policy. Many other sciences have oriented their agenda to issues related to global warming, and are now also identified as ‘environmental sciences.’

1. Ecology

1.1 Alexander Von Humboldt

Alexander von Humboldt (1769–1857) had received a university education in geology. An Inspector of Mines, he was embarking on a career in the service of the Prussian government, when the inheritance of his family fortune enabled him to give up his position. By then, he had been in contact with the naturalists on board of Captain James Cook’s scientific expeditions in the Pacific. In 1798, Humboldt began his own journey to Latin America. Upon his return in 1804, he became the most famous man in Europe after Napoleon. Travel and naturalistic research in the tropics were given an enormous boost through the accounts of his voyage. Among Humboldt’s many admirers may be counted the Dutch King and government, who sent a scientific expedition on a journey through Java in 1820, a first in Dutch colonial history.

1.2 Humboldtian Ecology

An important conceptual innovation of Alexander von Humboldt’s was the transformation of ‘landscape’ into a subject matter for science. Previously, the word landscape referred to a particular genre in painting, and Humboldt made good use of the painterly gaze, which confers unity on what it sees. Humboldt thus grasped the landscape in effect as an individual being. Every region of the globe had its own visual characteristics and beauty. Foremost in the appearance of a landscape was its ‘vegetation,’ another new concept, since it grouped plants according to the place where they lived rather than following their taxonomical order. Humboldt discovered that very different species not only occurred together, but that there were social relations among them, and he called these groupings of plants ‘associations’ (Nicolson 1987).

The first modern textbook of ecology by the Danish botanist Eugenius Warming appeared in 1895, with the English translation appearing in 1909. Warming retained Humboldt’s original precepts on plants in social associations. He worked them out in a precise manner, exposing the diversity of degrees and styles of interdependence, which exist in nature. Josias BraunBlanquet in Montpellier pursued this line of thought, and he and others in the so-called Zurich–Montpellier school produced a comprehensive system of Europe’s plant associations. This vegetation science would play a major role in the ecological underpinning of nature conservation practices in many countries of continental Europe (Nicolson 1989). Workers in the Zurich– Montpellier school could identify which rare species belong to a certain association—hence they knew when their nonoccurrence should cause concern. In the UK, a vegetation ecology of a different style has been equally useful for nature conservation, and its practitioners were consulted by the government to designate nature reserves since the late 1940s (Bowler 1992).

1.3 Darwin And Evolutionary Ecology

Charles Darwin’s famous Origin of Species of 1859 is as much an ecological book as it is about evolutionary theory. Darwin owed much to Humboldt’s holistic ecology, as Darwin saw the various species of animals and plants forming an ‘entangled’ whole. But whereas Humboldt stressed harmony in nature, Darwin regarded nature much more as a creative force. Nature continually disturbs settled equilibrium through the struggle of species scrambling for a place (Worster 1985). Evolutionary ecologists stress interactions between species (populations). They do not regard the climate as the deterministic factor in the make-up of animal communities, as ecosystem ecologists tend to do.

Population dynamics has strong ties with applied ecology: economic entomology (the study of pest insects in agriculture), and fishery ecology. Already by 1900, ecologists were working on biological pest control, that is, the method of holding one insect species in check by another. The publication of Silent Spring gave this research an important political boost (Perkins 1982, Palladino 1993).

Several approaches in population dynamics, in particular those of Robert May and C. vs. Holling, have enlarged its theoretical basis in diverse ways. Both developed new mathematical techniques, which tackled the occurrence of more or less dramatic changes in ecological systems. Though interesting leads exist with regard to nature conservation, notably in the work of Daniel Botkin, evolutionary ecology has been so far less influential in this domain than systems ecology.

1.4 Ecosystems And Systems Ecology

Systems ecology is the mathematical, computerimplemented form of ecosystem ecology. The latter assumes that large entities such as landscapes are functionally integrated wholes and it attempts to uncover their structure and functioning.

The word ‘ecosystem’ was coined in 1935 by Arthur Tansley, a British ecologist. Tansley wanted to place the older association or community oriented ecology on a mechanistic footing. This idea remained largely programmatic until the 1950s, when Eugene Odum pulled together some theoretical approaches and physical methodologies. Odum’s synthesis launched ecosystem ecology. It incorporated an emphasis on ‘productivity,’ which was added to the analysis of food web relations first pioneered by Charles Elton in the UK. Odum made use of newly available physical methodologies, most importantly the use of radioactive tracers. His approach was based on a recent discovery that several species accumulate radioactive isotopes, as they get picked up in minute quantities from the environment. Radioactive tracers permitted the elucidation of food webs both qualitatively (who eats what) and quantitatively (Kwa 1993).

The next step was to turn these quantified systems of food web relations into a more formal model that could be implemented on a computer. Through computer simulation of ecosystem models Odum’s fellow ecosystem ecologists hoped to find the key to the rational exploitation and control of natural resources. They hoped to use the models to help them establish the conditions under which ecosystems preserve their stability and to identify the natural mechanisms that enable them to do so.

The first model of a complete ecosystem was built in 1959, an electric model, a material analog of an ecosystem. The electrical current was the equivalent of the carbon cycle; resistors were the equivalents of various categories of groups of plants and animals, etc. The first whole ecosystem model, implemented on a digital computer, followed in 1965. These models were then gradually expanded in order to achieve closer similarity with real ecosystems. Their mathematical complexity in terms of the number of variables reached a temporary zenith in 1973. It was hoped that the models would mimic the behavior of real ecosystems at the scale of a good part of a continent. This expectation may now seem naive, but we may note that during the period 1959–1973 mainframe computers gradually became accessible to larger segments of the academic community. Many expected to use this expanded computing capacity to find the solutions to hitherto unsolvable complex problems. The prime example here is the ‘Limits to Growth’ model developed by Dennis Meadows for the Club of Rome in 1972 (Ashley 1983).

One important assumption built into the models was that ecosystems would be steered by climatic factors such as precipitation, temperature, and hours of sunshine. The models thus represented ecosystems as automatically steered machines, which would return to equilibrium after not too big a disturbance. However, if the functioning of the ecosystem was threatened, the ecosystem manager should make sure that equilibrium was safely reached again.

Around 1967, the US Congress became convinced that systems ecologists would be able to develop an early warning system, so that natural catastrophes could be avoided. The environmental movement also placed much trust in ecology as the science that could save humanity from its own excesses. Everywhere in the western world, measures to promote environmental hygiene were framed in a systems ecological vocabulary. As early as 1971, ecologists began to feel the pressure of popularity and increasingly voiced disclaimers about their ability ‘to save the planet.’

But by then professional ecologists were no longer needed for this purpose. Systems ecology had placed an emphasis on the circulation of matter and energy in the ecosystem, and other sciences could now push ahead with charting the various cycles of chemical substances to frame problems of pollution abatement and energy conservation. Another case in point is the carbon cycle, which at one point was understood as an ecological concept and which now has become a subject matter of meteorology.

2. Meteorology

Humboldt had invented the isotherms, lines on a map, which connect points with equal mean temperature. Together with isobars and a number of other graphic representations, such as of storm tracks, isotherms formed the basis of weather forecasting well into the twentieth century. Progress in meteorology was based on an ever-expanding system of atmospheric measurements. But the skillful combination of those involved many rules of thumb.

2.1 Vilhelm Bjerknes And The Bergen School Of Meteorology

Modern meteorology was founded by Vilhelm Bjerknes and his ‘Bergen school’ in Norway. He visualized the atmosphere as consisting of three- dimensional air masses moving around the globe, different in temperature, density, and humidity. An important step was achieved by Bjerknes’ son Jacob, who developed a model of the extra-tropical cyclone and how it moves. Bjerknes was able to exploit an existing military observational network for weather forecasting in western Norway, as it enabled him to follow the movement of the cyclones. It brought him considerable popular support in the area. The major breakthrough occurred in 1919, when the concept of the ‘polar front’ was born. It would take several decades before the world’s meteorologists were persuaded to ‘see’ a battle line, separating cold air masses from the north and warm air masses from the south. Bjerknes thought that this line stretched along the entire Atlantic, or indeed around the entire globe. Along the polar front the cyclones, or low-pressure areas, were formed, which would hit the coasts of Europe with rain and storm. Bjerknes put weather forecasting on a new footing. The analysis of polar fronts for the purpose of forecasting relied on large networks for atmospheric data gathering. Bjerknes pushed for it internationally, thereby also promoting the Bergen school ideas (Friedman 1989).

2.2 The Adoption Of The Bergen School Ideas In The US

The Bergen school ideas received a decisive boost when Carl-Gustav Rossby (b. 1898), a Swede who had worked with Bjerknes in Bergen, came to work at the US Weather Bureau during 1926–1927. He encountered stiff resistance to the Bergen school ideas, but he was able to recruit some followers.

In the late 1930s Rossby, by then at MIT, developed a method of calculating the large-scale motion of the atmosphere, based on the movement of long waves (later to be called Rossby waves). He put the westward movement of the extra-tropical cyclones more rigorously into the context of the general circulation of the Earth’s atmosphere, thus explaining semiquantitatively how the cyclones moved. On the basis of Rossby’s work, precision in forecasting methods was greatly enhanced in succeeding years.

2.3 Numerical Prediction Of The Weather On The Computer

John von Neumann, a mathematician, is one of the main architects of the modern computer. During World War II he had been working on the atom bomb at Los Alamos. After the war he initiated a project to build an ‘all-purpose, automatic, high speed electronic computing machine.’ Von Neumann also formulated the problems that computers were to solve among them the modeling of the atmosphere. The reason why von Neumann chose meteorology may have been the military importance of weather forecasts. Jule Charney became von Neumann’s collaborator in 1948. In early April 1950, the first successful numerical weather prediction was completed on the basis of Charney’s simple two-dimensional model of the atmosphere. Routine numerical weather prediction began by 1955.

The early models by Charney were intellectually derived from the Bergen school. However, in the mid-1960s these models were replaced in daily forecasting by models based on the so-called primitive equations which were basic physical equations describing the atmosphere. As a result, the original Bergen ‘fronts’ moved to the background in numerical meteorology.

2.4 The Attempt To Modify The Weather And The Climate

Between 1946 and 1973, there was a brief flourishing of the field of weather and climate modification. In 1946, Vincent Schaeffer and Irving Langmuir, working for General Electric in the US, discovered by chance that small quantities of frozen carbon dioxide could induce a cloud to release its contents. The many experiments that followed had a simple experimental format: clouds were sprayed with a reagent (most often silver iodide), usually from an airplane (Byers 1974). By 1965, just enough progress had been achieved in the eyes of the larger scientific community to endorse the idea of weather modification. Also, mergers took place between experimental cloud seeding and theoretical modeling of clouds and the atmosphere. One of these projects had been initiated at the National Hurricane Research Laboratory in Miami, which in 1963 had seeded two hurricanes. Results were evaluated as ‘encouraging if not conclusive.’ Around the same time, the US and the UK began to worry about Soviet plans to divert Siberian rivers away from their flow into the Northern Ice Sea. The West’s need for its own expertise on this matter provided an important impetus for the development of General Circulation Models of the whole Earth’s atmosphere.

Ten years later, funding for weather and climate modification was considerably reduced, despite the meteorologists continuing best efforts. But opposition had grown. There was increasing pressure by environmental activists against cloud seeding. Also, projected figures of jet exhausts of supersonic aircraft induced worries about anthropogenic damage to the ozone layer. In general, the long prevalent optimism about human interference in the environment was giving way to fears of irreparable damage.

3. Global Warming And Climate Change

Fear of unintended catastrophe is at the heart of the current concern about global warming. Never before has science revealed a risk, which is at once of such tremendous proportions and is surrounded by so many uncertainties (Jasanoff and Wynne 1998).

The General Circulation Models of the Earth’s atmosphere provide the primary evidence for the existence of a tendency toward global warming, later reconceptualized as climate change, and also that it is primarily caused by the human use of fossil fuels. The evidence is assessed by the Intergovernmental Panel on Climate Change (IPCC), an international body of scientific experts appointed by national governments to provide policy-relevant advice. The IPCC’s aim to seek broad consensus around scientific matters is contested by some scientists. To others, it is justified because the stakes are so high.

General Circulation Models are now becoming linked to models of the oceans, and the influence on the atmosphere by the vegetation masses of the earth is under investigation. If research on the causes of global warming exceed the disciplinary limits of meteorology, research on the possible effects of global climate change has drawn in a still larger cross-section of the sciences. Physical geography, regional planning, ecology, and environmental economics assess the impact of global warming on land-use and the landscape. A new science of integrated assessment has sprung up, which researches ways to combine all the available knowledge into so-called ‘Integrated Assessment Models.’ Models of this kind were used to advise the European Commission in proposing targets for energy-use reduction at the international negotiations in Kyoto, 1998.

Models appear to be the instrument of choice to master the complexity of the environment. Their range is wide, with scopes extending from the General Circulation Models to changes in the Delta of the Rhine as the expected result of increased rainfall caused by global warming. Over the past decades, the mathematical sophistication of models has been greatly improved, as have been the computers on which they are run. Yet, expectations with regard to precision in forecasting and the extent of possible human control over the environment have diminished in important respects as awareness of complexity and uncertainty has grown. Models of the environment have become highly ambiguous things, and it is easiest to say what they are not: truthful pictures of the world as it is and how it will evolve (Shackley 1997). Scientists usually take models as tools for further research, while policy makers need them to base their decisions on. Contested as they may be, models increasingly function as mediators between the environmental sciences and society.


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